1ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov//--------------------------------------------------------------------------------- 2ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 3ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Little Color Management System 4ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Copyright (c) 1998-2013 Marti Maria Saguer 5ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 6ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Permission is hereby granted, free of charge, to any person obtaining 7ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// a copy of this software and associated documentation files (the "Software"), 8ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// to deal in the Software without restriction, including without limitation 9ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// the rights to use, copy, modify, merge, publish, distribute, sublicense, 10ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// and/or sell copies of the Software, and to permit persons to whom the Software 11ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// is furnished to do so, subject to the following conditions: 12ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 13ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The above copyright notice and this permission notice shall be included in 14ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// all copies or substantial portions of the Software. 15ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 16ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, 17ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO 18ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND 19ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE 20ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION 21ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION 22ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. 23ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 24ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov//--------------------------------------------------------------------------------- 25ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 26ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 27ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov#include "lcms2_internal.h" 28ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 29ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Tone curves are powerful constructs that can contain curves specified in diverse ways. 30ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The curve is stored in segments, where each segment can be sampled or specified by parameters. 31ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// a 16.bit simplification of the *whole* curve is kept for optimization purposes. For float operation, 32ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// each segment is evaluated separately. Plug-ins may be used to define new parametric schemes, 33ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// each plug-in may define up to MAX_TYPES_IN_LCMS_PLUGIN functions types. For defining a function, 34ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// the plug-in should provide the type id, how many parameters each type has, and a pointer to 35ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// a procedure that evaluates the function. In the case of reverse evaluation, the evaluator will 36ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// be called with the type id as a negative value, and a sampled version of the reversed curve 37ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// will be built. 38ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 39ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// ----------------------------------------------------------------- Implementation 40ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Maxim number of nodes 41ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov#define MAX_NODES_IN_CURVE 4097 42ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov#define MINUS_INF (-1E22F) 43ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov#define PLUS_INF (+1E22F) 44ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 45ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The list of supported parametric curves 46ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovtypedef struct _cmsParametricCurvesCollection_st { 47ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 48ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int nFunctions; // Number of supported functions in this chunk 49ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types 50ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int ParameterCount[MAX_TYPES_IN_LCMS_PLUGIN]; // Number of parameters for each function 51ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsParametricCurveEvaluator Evaluator; // The evaluator 52ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 53ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov struct _cmsParametricCurvesCollection_st* Next; // Next in list 54ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 55ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} _cmsParametricCurvesCollection; 56ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 57ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// This is the default (built-in) evaluator 58ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R); 59ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 60ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The built-in list 61ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic _cmsParametricCurvesCollection DefaultCurves = { 62ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 9, // # of curve types 63ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 1, 2, 3, 4, 5, 6, 7, 8, 108 }, // Parametric curve ID 64ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 1, 3, 4, 5, 7, 4, 5, 5, 1 }, // Parameters by type 65ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov DefaultEvalParametricFn, // Evaluator 66ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov NULL // Next in chain 67ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov}; 68ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 69ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Duplicates the zone of memory used by the plug-in in the new context 70ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 71ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovvoid DupPluginCurvesList(struct _cmsContext_struct* ctx, 72ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov const struct _cmsContext_struct* src) 73ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 74ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsCurvesPluginChunkType newHead = { NULL }; 75ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection* entry; 76ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection* Anterior = NULL; 77ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsCurvesPluginChunkType* head = (_cmsCurvesPluginChunkType*) src->chunks[CurvesPlugin]; 78ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 79ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(head != NULL); 80ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 81ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Walk the list copying all nodes 82ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (entry = head->ParametricCurves; 83ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov entry != NULL; 84ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov entry = entry ->Next) { 85ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 86ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection *newEntry = ( _cmsParametricCurvesCollection *) _cmsSubAllocDup(ctx ->MemPool, entry, sizeof(_cmsParametricCurvesCollection)); 87ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 88ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (newEntry == NULL) 89ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return; 90ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 91ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // We want to keep the linked list order, so this is a little bit tricky 92ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov newEntry -> Next = NULL; 93ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Anterior) 94ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Anterior -> Next = newEntry; 95ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 96ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Anterior = newEntry; 97ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 98ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (newHead.ParametricCurves == NULL) 99ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov newHead.ParametricCurves = newEntry; 100ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 101ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 102ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx->MemPool, &newHead, sizeof(_cmsCurvesPluginChunkType)); 103ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 104ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 105ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The allocator have to follow the chain 106ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovvoid _cmsAllocCurvesPluginChunk(struct _cmsContext_struct* ctx, 107ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov const struct _cmsContext_struct* src) 108ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 109ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(ctx != NULL); 110ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 111ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (src != NULL) { 112ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 113ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Copy all linked list 114ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov DupPluginCurvesList(ctx, src); 115ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 116ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 117ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov static _cmsCurvesPluginChunkType CurvesPluginChunk = { NULL }; 118ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx ->MemPool, &CurvesPluginChunk, sizeof(_cmsCurvesPluginChunkType)); 119ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 120ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 121ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 122ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 123ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The linked list head 124ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov_cmsCurvesPluginChunkType _cmsCurvesPluginChunk = { NULL }; 125ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 126ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// As a way to install new parametric curves 127ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool _cmsRegisterParametricCurvesPlugin(cmsContext ContextID, cmsPluginBase* Data) 128ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 129ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin); 130ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsPluginParametricCurves* Plugin = (cmsPluginParametricCurves*) Data; 131ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection* fl; 132ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 133ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Data == NULL) { 134ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 135ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov ctx -> ParametricCurves = NULL; 136ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return TRUE; 137ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 138ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 139ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov fl = (_cmsParametricCurvesCollection*) _cmsPluginMalloc(ContextID, sizeof(_cmsParametricCurvesCollection)); 140ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (fl == NULL) return FALSE; 141ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 142ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Copy the parameters 143ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov fl ->Evaluator = Plugin ->Evaluator; 144ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov fl ->nFunctions = Plugin ->nFunctions; 145ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 146ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Make sure no mem overwrites 147ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (fl ->nFunctions > MAX_TYPES_IN_LCMS_PLUGIN) 148ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov fl ->nFunctions = MAX_TYPES_IN_LCMS_PLUGIN; 149ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 150ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Copy the data 151ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memmove(fl->FunctionTypes, Plugin ->FunctionTypes, fl->nFunctions * sizeof(cmsUInt32Number)); 152ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memmove(fl->ParameterCount, Plugin ->ParameterCount, fl->nFunctions * sizeof(cmsUInt32Number)); 153ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 154ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Keep linked list 155ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov fl ->Next = ctx->ParametricCurves; 156ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov ctx->ParametricCurves = fl; 157ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 158ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // All is ok 159ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return TRUE; 160ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 161ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 162ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 163ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Search in type list, return position or -1 if not found 164ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 165ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovint IsInSet(int Type, _cmsParametricCurvesCollection* c) 166ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 167ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i; 168ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 169ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < c ->nFunctions; i++) 170ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (abs(Type) == c ->FunctionTypes[i]) return i; 171ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 172ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return -1; 173ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 174ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 175ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 176ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Search for the collection which contains a specific type 177ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 178ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov_cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index) 179ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 180ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection* c; 181ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int Position; 182ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin); 183ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 184ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (c = ctx->ParametricCurves; c != NULL; c = c ->Next) { 185ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 186ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Position = IsInSet(Type, c); 187ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 188ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Position != -1) { 189ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (index != NULL) 190ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov *index = Position; 191ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return c; 192ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 193ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 194ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // If none found, revert for defaults 195ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (c = &DefaultCurves; c != NULL; c = c ->Next) { 196ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 197ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Position = IsInSet(Type, c); 198ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 199ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Position != -1) { 200ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (index != NULL) 201ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov *index = Position; 202ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return c; 203ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 204ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 205ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 206ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 207ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 208ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 209ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Low level allocate, which takes care of memory details. nEntries may be zero, and in this case 210ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// no optimation curve is computed. nSegments may also be zero in the inverse case, where only the 211ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// optimization curve is given. Both features simultaneously is an error 212ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 213ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* AllocateToneCurveStruct(cmsContext ContextID, cmsInt32Number nEntries, 214ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsInt32Number nSegments, const cmsCurveSegment* Segments, 215ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov const cmsUInt16Number* Values) 216ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 217ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsToneCurve* p; 218ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i; 219ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 220ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // We allow huge tables, which are then restricted for smoothing operations 221ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nEntries > 65530 || nEntries < 0) { 222ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve of more than 65530 entries"); 223ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 224ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 225ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 226ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nEntries <= 0 && nSegments <= 0) { 227ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve with zero segments and no table"); 228ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 229ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 230ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 231ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Allocate all required pointers, etc. 232ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p = (cmsToneCurve*) _cmsMallocZero(ContextID, sizeof(cmsToneCurve)); 233ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (!p) return NULL; 234ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 235ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // In this case, there are no segments 236ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nSegments <= 0) { 237ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Segments = NULL; 238ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Evals = NULL; 239ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 240ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 241ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Segments = (cmsCurveSegment*) _cmsCalloc(ContextID, nSegments, sizeof(cmsCurveSegment)); 242ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p ->Segments == NULL) goto Error; 243ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 244ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Evals = (cmsParametricCurveEvaluator*) _cmsCalloc(ContextID, nSegments, sizeof(cmsParametricCurveEvaluator)); 245ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p ->Evals == NULL) goto Error; 246ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 247ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 248ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p -> nSegments = nSegments; 249ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 250ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // This 16-bit table contains a limited precision representation of the whole curve and is kept for 251ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // increasing xput on certain operations. 252ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nEntries <= 0) { 253ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Table16 = NULL; 254ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 255ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 256ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Table16 = (cmsUInt16Number*) _cmsCalloc(ContextID, nEntries, sizeof(cmsUInt16Number)); 257ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p ->Table16 == NULL) goto Error; 258ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 259ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 260ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p -> nEntries = nEntries; 261ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 262ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Initialize members if requested 263ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Values != NULL && (nEntries > 0)) { 264ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 265ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nEntries; i++) 266ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Table16[i] = Values[i]; 267ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 268ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 269ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Initialize the segments stuff. The evaluator for each segment is located and a pointer to it 270ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // is placed in advance to maximize performance. 271ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Segments != NULL && (nSegments > 0)) { 272ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 273ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection *c; 274ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 275ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->SegInterp = (cmsInterpParams**) _cmsCalloc(ContextID, nSegments, sizeof(cmsInterpParams*)); 276ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p ->SegInterp == NULL) goto Error; 277ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 278ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i< nSegments; i++) { 279ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 280ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 0 is a special marker for table-based curves 281ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Segments[i].Type == 0) 282ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->SegInterp[i] = _cmsComputeInterpParams(ContextID, Segments[i].nGridPoints, 1, 1, NULL, CMS_LERP_FLAGS_FLOAT); 283ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 284ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memmove(&p ->Segments[i], &Segments[i], sizeof(cmsCurveSegment)); 285ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 286ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Segments[i].Type == 0 && Segments[i].SampledPoints != NULL) 287ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Segments[i].SampledPoints = (cmsFloat32Number*) _cmsDupMem(ContextID, Segments[i].SampledPoints, sizeof(cmsFloat32Number) * Segments[i].nGridPoints); 288ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 289ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Segments[i].SampledPoints = NULL; 290ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 291ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 292ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c = GetParametricCurveByType(ContextID, Segments[i].Type, NULL); 293ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (c != NULL) 294ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->Evals[i] = c ->Evaluator; 295ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 296ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 297ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 298ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov p ->InterpParams = _cmsComputeInterpParams(ContextID, p ->nEntries, 1, 1, p->Table16, CMS_LERP_FLAGS_16BITS); 299ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p->InterpParams != NULL) 300ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return p; 301ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 302ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovError: 303ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p -> Segments) _cmsFree(ContextID, p ->Segments); 304ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p -> Evals) _cmsFree(ContextID, p -> Evals); 305ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p ->Table16) _cmsFree(ContextID, p ->Table16); 306ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, p); 307ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 308ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 309ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 310ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 311ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Parametric Fn using floating point 312ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 313ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R) 314ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 315ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat64Number e, Val, disc; 316ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 317ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov switch (Type) { 318ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 319ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X = Y ^ Gamma 320ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 1: 321ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R < 0) { 322ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 323ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) 324ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = R; 325ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 326ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 327ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 328ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 329ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(R, Params[0]); 330ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 331ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 332ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 1 Reversed: X = Y ^1/gamma 333ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -1: 334ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R < 0) { 335ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 336ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) 337ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = R; 338ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 339ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 340ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 341ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 342ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(R, 1/Params[0]); 343ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 344ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 345ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // CIE 122-1966 346ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (aX + b)^Gamma | X >= -b/a 347ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = 0 | else 348ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 2: 349ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = -Params[2] / Params[1]; 350ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 351ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= disc ) { 352ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 353ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1]*R + Params[2]; 354ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 355ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e > 0) 356ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(e, Params[0]); 357ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 358ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 359ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 360ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 361ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 362ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 363ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 364ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 2 Reversed 365ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X = (Y ^1/g - b) / a 366ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -2: 367ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R < 0) 368ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 369ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 370ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (pow(R, 1.0/Params[0]) - Params[2]) / Params[1]; 371ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 372ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Val < 0) 373ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 374ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 375ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 376ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 377ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // IEC 61966-3 378ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (aX + b)^Gamma | X <= -b/a 379ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = c | else 380ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 3: 381ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = -Params[2] / Params[1]; 382ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (disc < 0) 383ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = 0; 384ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 385ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= disc) { 386ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 387ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1]*R + Params[2]; 388ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 389ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e > 0) 390ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(e, Params[0]) + Params[3]; 391ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 392ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 393ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 394ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 395ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = Params[3]; 396ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 397ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 398ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 399ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 3 reversed 400ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=((Y-c)^1/g - b)/a | (Y>=c) 401ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=-b/a | (Y<c) 402ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -3: 403ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= Params[3]) { 404ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 405ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = R - Params[3]; 406ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 407ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e > 0) 408ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (pow(e, 1/Params[0]) - Params[2]) / Params[1]; 409ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 410ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 411ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 412ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 413ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = -Params[2] / Params[1]; 414ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 415ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 416ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 417ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 418ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // IEC 61966-2.1 (sRGB) 419ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (aX + b)^Gamma | X >= d 420ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = cX | X < d 421ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 4: 422ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= Params[4]) { 423ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 424ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1]*R + Params[2]; 425ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 426ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e > 0) 427ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(e, Params[0]); 428ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 429ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 430ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 431ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 432ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = R * Params[3]; 433ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 434ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 435ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 4 reversed 436ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=((Y^1/g-b)/a) | Y >= (ad+b)^g 437ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=Y/c | Y< (ad+b)^g 438ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -4: 439ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1] * Params[4] + Params[2]; 440ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e < 0) 441ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = 0; 442ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 443ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = pow(e, Params[0]); 444ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 445ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= disc) { 446ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 447ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (pow(R, 1.0/Params[0]) - Params[2]) / Params[1]; 448ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 449ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 450ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = R / Params[3]; 451ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 452ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 453ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 454ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 455ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (aX + b)^Gamma + e | X >= d 456ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = cX + f | X < d 457ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 5: 458ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= Params[4]) { 459ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 460ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1]*R + Params[2]; 461ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 462ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e > 0) 463ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(e, Params[0]) + Params[5]; 464ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 465ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = Params[5]; 466ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 467ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 468ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = R*Params[3] + Params[6]; 469ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 470ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 471ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 472ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Reversed type 5 473ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f 474ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // X=(Y-f)/c | else 475ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -5: 476ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 477ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = Params[3] * Params[4] + Params[6]; 478ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (R >= disc) { 479ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 480ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = R - Params[5]; 481ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e < 0) 482ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 483ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 484ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (pow(e, 1.0/Params[0]) - Params[2]) / Params[1]; 485ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 486ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 487ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (R - Params[6]) / Params[3]; 488ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 489ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 490ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 491ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 492ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf 493ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type 6 is basically identical to type 5 without d 494ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 495ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (a * X + b) ^ Gamma + c 496ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 6: 497ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[1]*R + Params[2]; 498ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 499ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e < 0) 500ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = Params[3]; 501ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 502ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(e, Params[0]) + Params[3]; 503ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 504ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 505ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // ((Y - c) ^1/Gamma - b) / a 506ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -6: 507ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = R - Params[3]; 508ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e < 0) 509ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 0; 510ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 511ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (pow(e, 1.0/Params[0]) - Params[2]) / Params[1]; 512ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 513ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 514ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 515ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = a * log (b * X^Gamma + c) + d 516ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 7: 517ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 518ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = Params[2] * pow(R, Params[0]) + Params[3]; 519ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e <= 0) 520ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = Params[4]; 521ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 522ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = Params[1]*log10(e) + Params[4]; 523ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 524ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 525ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // (Y - d) / a = log(b * X ^Gamma + c) 526ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // pow(10, (Y-d) / a) = b * X ^Gamma + c 527ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X 528ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -7: 529ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow((pow(10.0, (R-Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]); 530ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 531ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 532ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 533ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov //Y = a * b^(c*X+d) + e 534ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 8: 535ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]); 536ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 537ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 538ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 539ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Y = (log((y-e) / a) / log(b) - d ) / c 540ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // a=0, b=1, c=2, d=3, e=4, 541ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -8: 542ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 543ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov disc = R - Params[4]; 544ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (disc < 0) Val = 0; 545ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 546ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2]; 547ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 548ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 549ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // S-Shaped: (1 - (1-x)^1/g)^1/g 550ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case 108: 551ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]); 552ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 553ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 554ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // y = (1 - (1-x)^1/g)^1/g 555ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // y^g = (1 - (1-x)^1/g) 556ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // 1 - y^g = (1-x)^1/g 557ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // (1 - y^g)^g = 1 - x 558ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // 1 - (1 - y^g)^g 559ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov case -108: 560ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = 1 - pow(1 - pow(R, Params[0]), Params[0]); 561ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov break; 562ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 563ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov default: 564ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Unsupported parametric curve. Should never reach here 565ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return 0; 566ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 567ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 568ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return Val; 569ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 570ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 571ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Evaluate a segmented funtion for a single value. Return -1 if no valid segment found . 572ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// If fn type is 0, perform an interpolation on the table 573ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 574ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsFloat64Number EvalSegmentedFn(const cmsToneCurve *g, cmsFloat64Number R) 575ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 576ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i; 577ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 578ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i = g ->nSegments-1; i >= 0 ; --i) { 579ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 580ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Check for domain 581ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if ((R > g ->Segments[i].x0) && (R <= g ->Segments[i].x1)) { 582ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 583ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Type == 0 means segment is sampled 584ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (g ->Segments[i].Type == 0) { 585ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 586ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number R1 = (cmsFloat32Number) (R - g ->Segments[i].x0) / (g ->Segments[i].x1 - g ->Segments[i].x0); 587ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number Out; 588ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 589ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Setup the table (TODO: clean that) 590ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov g ->SegInterp[i]-> Table = g ->Segments[i].SampledPoints; 591ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 592ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov g ->SegInterp[i] -> Interpolation.LerpFloat(&R1, &Out, g ->SegInterp[i]); 593ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 594ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return Out; 595ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 596ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 597ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return g ->Evals[i](g->Segments[i].Type, g ->Segments[i].Params, R); 598ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 599ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 600ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 601ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return MINUS_INF; 602ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 603ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 604ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Access to estimated low-res table 605ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve* t) 606ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 607ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 608ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return t ->nEntries; 609ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 610ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 611ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovconst cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(const cmsToneCurve* t) 612ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 613ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 614ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return t ->Table16; 615ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 616ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 617ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 618ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the 619ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// floating point description empty. 620ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsInt32Number nEntries, const cmsUInt16Number Values[]) 621ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 622ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values); 623ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 624ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 625ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 626ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovint EntriesByGamma(cmsFloat64Number Gamma) 627ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 628ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (fabs(Gamma - 1.0) < 0.001) return 2; 629ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return 4096; 630ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 631ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 632ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 633ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Create a segmented gamma, fill the table 634ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID, 635ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsInt32Number nSegments, const cmsCurveSegment Segments[]) 636ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 637ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i; 638ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat64Number R, Val; 639ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsToneCurve* g; 640ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int nGridPoints = 4096; 641ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 642ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Segments != NULL); 643ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 644ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Optimizatin for identity curves. 645ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nSegments == 1 && Segments[0].Type == 1) { 646ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 647ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov nGridPoints = EntriesByGamma(Segments[0].Params[0]); 648ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 649ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 650ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL); 651ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (g == NULL) return NULL; 652ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 653ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Once we have the floating point version, we can approximate a 16 bit table of 4096 entries 654ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // for performance reasons. This table would normally not be used except on 8/16 bits transforms. 655ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nGridPoints; i++) { 656ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 657ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov R = (cmsFloat64Number) i / (nGridPoints-1); 658ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 659ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Val = EvalSegmentedFn(g, R); 660ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 661ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Round and saturate 662ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0); 663ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 664ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 665ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return g; 666ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 667ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 668ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Use a segmented curve to store the floating point table 669ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[]) 670ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 671ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsCurveSegment Seg[3]; 672ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 673ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // A segmented tone curve should have function segments in the first and last positions 674ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Initialize segmented curve part up to 0 to constant value = samples[0] 675ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].x0 = MINUS_INF; 676ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].x1 = 0; 677ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Type = 6; 678ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 679ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Params[0] = 1; 680ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Params[1] = 0; 681ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Params[2] = 0; 682ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Params[3] = values[0]; 683ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[0].Params[4] = 0; 684ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 685ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // From zero to 1 686ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[1].x0 = 0; 687ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[1].x1 = 1.0; 688ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[1].Type = 0; 689ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 690ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[1].nGridPoints = nEntries; 691ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[1].SampledPoints = (cmsFloat32Number*) values; 692ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 693ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Final segment is constant = lastsample 694ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].x0 = 1.0; 695ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].x1 = PLUS_INF; 696ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Type = 6; 697ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 698ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Params[0] = 1; 699ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Params[1] = 0; 700ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Params[2] = 0; 701ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Params[3] = values[nEntries-1]; 702ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg[2].Params[4] = 0; 703ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 704ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 705ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return cmsBuildSegmentedToneCurve(ContextID, 3, Seg); 706ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 707ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 708ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Parametric curves 709ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 710ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Parameters goes as: Curve, a, b, c, d, e, f 711ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Type is the ICC type +1 712ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// if type is negative, then the curve is analyticaly inverted 713ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[]) 714ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 715ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsCurveSegment Seg0; 716ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int Pos = 0; 717ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt32Number size; 718ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos); 719ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 720ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Params != NULL); 721ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 722ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (c == NULL) { 723ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type); 724ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 725ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 726ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 727ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memset(&Seg0, 0, sizeof(Seg0)); 728ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 729ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg0.x0 = MINUS_INF; 730ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg0.x1 = PLUS_INF; 731ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Seg0.Type = Type; 732ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 733ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number); 734ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memmove(Seg0.Params, Params, size); 735ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 736ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0); 737ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 738ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 739ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 740ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 741ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Build a gamma table based on gamma constant 742ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma) 743ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 744ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return cmsBuildParametricToneCurve(ContextID, 1, &Gamma); 745ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 746ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 747ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 748ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Free all memory taken by the gamma curve 749ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovvoid CMSEXPORT cmsFreeToneCurve(cmsToneCurve* Curve) 750ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 751ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsContext ContextID; 752ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 753ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // added by Xiaochuan Liu 754ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Curve->InterpParams may be null 755ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve == NULL || Curve->InterpParams == NULL) return; 756ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 757ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov ContextID = Curve ->InterpParams->ContextID; 758ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 759ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFreeInterpParams(Curve ->InterpParams); 760ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->InterpParams = NULL; 761ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 762ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve -> Table16) 763ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 764ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve ->Table16); 765ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->Table16 = NULL; 766ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 767ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 768ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve ->Segments) { 769ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 770ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt32Number i; 771ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 772ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < Curve ->nSegments; i++) { 773ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 774ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve ->Segments[i].SampledPoints) { 775ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve ->Segments[i].SampledPoints); 776ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->Segments[i].SampledPoints = NULL; 777ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 778ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 779ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve ->SegInterp[i] != 0) 780ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 781ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFreeInterpParams(Curve->SegInterp[i]); 782ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve->SegInterp[i] = NULL; 783ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 784ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 785ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 786ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve ->Segments); 787ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->Segments = NULL; 788ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve ->SegInterp); 789ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->SegInterp = NULL; 790ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 791ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 792ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve -> Evals) 793ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 794ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve -> Evals); 795ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve -> Evals = NULL; 796ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 797ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 798ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve) 799ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 800ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsFree(ContextID, Curve); 801ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve = NULL; 802ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 803ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 804ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 805ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Utility function, free 3 gamma tables 806ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovvoid CMSEXPORT cmsFreeToneCurveTriple(cmsToneCurve* Curve[3]) 807ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 808ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 809ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Curve != NULL); 810ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 811ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve[0] != NULL) cmsFreeToneCurve(Curve[0]); 812ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve[1] != NULL) cmsFreeToneCurve(Curve[1]); 813ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve[2] != NULL) cmsFreeToneCurve(Curve[2]); 814ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 815ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve[0] = Curve[1] = Curve[2] = NULL; 816ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 817ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 818ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 819ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Duplicate a gamma table 820ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsDupToneCurve(const cmsToneCurve* In) 821ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 822ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Xiaochuan Liu 823ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // fix openpdf bug(mantis id:0055683, google id:360198) 824ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // the function CurveSetElemTypeFree in cmslut.c also needs to check pointer 825ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (In == NULL || In ->InterpParams == NULL) return NULL; 826ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 827ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return AllocateToneCurveStruct(In ->InterpParams ->ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16); 828ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 829ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 830ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Joins two curves for X and Y. Curves should be monotonic. 831ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// We want to get 832ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 833ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// y = Y^-1(X(t)) 834ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 835ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID, 836ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov const cmsToneCurve* X, 837ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov const cmsToneCurve* Y, cmsUInt32Number nResultingPoints) 838ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 839ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsToneCurve* out = NULL; 840ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsToneCurve* Yreversed = NULL; 841ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number t, x; 842ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number* Res = NULL; 843ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt32Number i; 844ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 845ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 846ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(X != NULL); 847ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Y != NULL); 848ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 849ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Yreversed = cmsReverseToneCurveEx(nResultingPoints, Y); 850ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Yreversed == NULL) goto Error; 851ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 852ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number)); 853ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Res == NULL) goto Error; 854ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 855ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov //Iterate 856ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nResultingPoints; i++) { 857ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 858ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov t = (cmsFloat32Number) i / (nResultingPoints-1); 859ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov x = cmsEvalToneCurveFloat(X, t); 860ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Res[i] = cmsEvalToneCurveFloat(Yreversed, x); 861ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 862ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 863ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Allocate space for output 864ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res); 865ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 866ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovError: 867ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 868ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Res != NULL) _cmsFree(ContextID, Res); 869ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Yreversed != NULL) cmsFreeToneCurve(Yreversed); 870ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 871ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return out; 872ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 873ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 874ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 875ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 876ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Get the surrounding nodes. This is tricky on non-monotonic tables 877ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 878ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovint GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p) 879ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 880ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i; 881ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int y0, y1; 882ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 883ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // A 1 point table is not allowed 884ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (p -> Domain[0] < 1) return -1; 885ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 886ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Let's see if ascending or descending. 887ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (LutTable[0] < LutTable[p ->Domain[0]]) { 888ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 889ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Table is overall ascending 890ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=p->Domain[0]-1; i >=0; --i) { 891ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 892ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y0 = LutTable[i]; 893ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y1 = LutTable[i+1]; 894ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 895ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (y0 <= y1) { // Increasing 896ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (In >= y0 && In <= y1) return i; 897ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 898ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 899ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (y1 < y0) { // Decreasing 900ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (In >= y1 && In <= y0) return i; 901ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 902ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 903ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 904ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 905ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Table is overall descending 906ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < (int) p -> Domain[0]; i++) { 907ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 908ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y0 = LutTable[i]; 909ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y1 = LutTable[i+1]; 910ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 911ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (y0 <= y1) { // Increasing 912ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (In >= y0 && In <= y1) return i; 913ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 914ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 915ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (y1 < y0) { // Decreasing 916ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (In >= y1 && In <= y0) return i; 917ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 918ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 919ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 920ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 921ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return -1; 922ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 923ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 924ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Reverse a gamma table 925ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsInt32Number nResultSamples, const cmsToneCurve* InCurve) 926ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 927ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsToneCurve *out; 928ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2; 929ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i, j; 930ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int Ascending; 931ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 932ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(InCurve != NULL); 933ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 934ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Try to reverse it analytically whatever possible 935ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 936ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 && 937ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov /* InCurve -> Segments[0].Type <= 5 */ 938ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov GetParametricCurveByType(InCurve ->InterpParams->ContextID, InCurve ->Segments[0].Type, NULL) != NULL) { 939ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 940ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return cmsBuildParametricToneCurve(InCurve ->InterpParams->ContextID, 941ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov -(InCurve -> Segments[0].Type), 942ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov InCurve -> Segments[0].Params); 943ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 944ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 945ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Nope, reverse the table. 946ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov out = cmsBuildTabulatedToneCurve16(InCurve ->InterpParams->ContextID, nResultSamples, NULL); 947ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (out == NULL) 948ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return NULL; 949ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 950ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // We want to know if this is an ascending or descending table 951ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Ascending = !cmsIsToneCurveDescending(InCurve); 952ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 953ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Iterate across Y axis 954ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nResultSamples; i++) { 955ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 956ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1); 957ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 958ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Find interval in which y is within. 959ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov j = GetInterval(y, InCurve->Table16, InCurve->InterpParams); 960ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (j >= 0) { 961ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 962ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 963ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Get limits of interval 964ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov x1 = InCurve ->Table16[j]; 965ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov x2 = InCurve ->Table16[j+1]; 966ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 967ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1); 968ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1); 969ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 970ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // If collapsed, then use any 971ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (x1 == x2) { 972ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 973ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1); 974ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov continue; 975ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 976ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } else { 977ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 978ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Interpolate 979ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov a = (y2 - y1) / (x2 - x1); 980ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov b = y2 - a * x2; 981ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 982ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 983ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 984ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov out ->Table16[i] = _cmsQuickSaturateWord(a* y + b); 985ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 986ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 987ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 988ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return out; 989ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 990ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 991ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Reverse a gamma table 992ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsToneCurve* CMSEXPORT cmsReverseToneCurve(const cmsToneCurve* InGamma) 993ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 994ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(InGamma != NULL); 995ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 996ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return cmsReverseToneCurveEx(4096, InGamma); 997ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 998ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 999ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite 1000ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press. 1001ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1002ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Smoothing and interpolation with second differences. 1003ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1004ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Input: weights (w), data (y): vector from 1 to m. 1005ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Input: smoothing parameter (lambda), length (m). 1006ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Output: smoothed vector (z): vector from 1 to m. 1007ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1008ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganovstatic 1009ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[], cmsFloat32Number z[], cmsFloat32Number lambda, int m) 1010ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1011ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i, i1, i2; 1012ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number *c, *d, *e; 1013ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsBool st; 1014ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1015ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1016ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1017ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1018ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); 1019ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1020ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (c != NULL && d != NULL && e != NULL) { 1021ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1022ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1023ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d[1] = w[1] + lambda; 1024ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c[1] = -2 * lambda / d[1]; 1025ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e[1] = lambda /d[1]; 1026ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[1] = w[1] * y[1]; 1027ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1]; 1028ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2]; 1029ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e[2] = lambda / d[2]; 1030ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[2] = w[2] * y[2] - c[1] * z[1]; 1031ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1032ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i = 3; i < m - 1; i++) { 1033ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov i1 = i - 1; i2 = i - 2; 1034ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1035ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i]; 1036ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov e[i] = lambda / d[i]; 1037ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2]; 1038ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1039ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1040ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov i1 = m - 2; i2 = m - 3; 1041ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1042ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1043ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1]; 1044ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2]; 1045ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov i1 = m - 1; i2 = m - 2; 1046ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1047ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; 1048ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m]; 1049ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m]; 1050ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1051ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i = m - 2; 1<= i; i--) 1052ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2]; 1053ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1054ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov st = TRUE; 1055ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1056ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else st = FALSE; 1057ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1058ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (c != NULL) _cmsFree(ContextID, c); 1059ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (d != NULL) _cmsFree(ContextID, d); 1060ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (e != NULL) _cmsFree(ContextID, e); 1061ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1062ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return st; 1063ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1064ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1065ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Smooths a curve sampled at regular intervals. 1066ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool CMSEXPORT cmsSmoothToneCurve(cmsToneCurve* Tab, cmsFloat64Number lambda) 1067ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1068ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat32Number w[MAX_NODES_IN_CURVE], y[MAX_NODES_IN_CURVE], z[MAX_NODES_IN_CURVE]; 1069ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i, nItems, Zeros, Poles; 1070ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1071ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Tab == NULL) return FALSE; 1072ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1073ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (cmsIsToneCurveLinear(Tab)) return TRUE; // Nothing to do 1074ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1075ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov nItems = Tab -> nEntries; 1076ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1077ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (nItems >= MAX_NODES_IN_CURVE) { 1078ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: too many points."); 1079ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1080ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1081ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1082ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memset(w, 0, nItems * sizeof(cmsFloat32Number)); 1083ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memset(y, 0, nItems * sizeof(cmsFloat32Number)); 1084ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov memset(z, 0, nItems * sizeof(cmsFloat32Number)); 1085ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1086ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nItems; i++) 1087ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov { 1088ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y[i+1] = (cmsFloat32Number) Tab -> Table16[i]; 1089ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov w[i+1] = 1.0; 1090ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1091ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1092ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (!smooth2(Tab ->InterpParams->ContextID, w, y, z, (cmsFloat32Number) lambda, nItems)) return FALSE; 1093ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1094ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Do some reality - checking... 1095ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Zeros = Poles = 0; 1096ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=nItems; i > 1; --i) { 1097ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1098ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (z[i] == 0.) Zeros++; 1099ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (z[i] >= 65535.) Poles++; 1100ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (z[i] < z[i-1]) { 1101ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic."); 1102ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1103ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1104ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1105ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1106ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Zeros > (nItems / 3)) { 1107ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros."); 1108ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1109ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1110ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Poles > (nItems / 3)) { 1111ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles."); 1112ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1113ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1114ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1115ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Seems ok 1116ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < nItems; i++) { 1117ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1118ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Clamp to cmsUInt16Number 1119ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Tab -> Table16[i] = _cmsQuickSaturateWord(z[i+1]); 1120ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1121ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1122ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return TRUE; 1123ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1124ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1125ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting 1126ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// in a linear table. This way assures it is linear in 12 bits, which should be enought in most cases. 1127ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve) 1128ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1129ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt32Number i; 1130ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int diff; 1131ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1132ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Curve != NULL); 1133ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1134ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=0; i < Curve ->nEntries; i++) { 1135ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1136ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries)); 1137ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (diff > 0x0f) 1138ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1139ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1140ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1141ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return TRUE; 1142ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1143ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1144ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Same, but for monotonicity 1145ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool CMSEXPORT cmsIsToneCurveMonotonic(const cmsToneCurve* t) 1146ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1147ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int n; 1148ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov int i, last; 1149ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsBool lDescending; 1150ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1151ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 1152ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1153ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Degenerated curves are monotonic? Ok, let's pass them 1154ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov n = t ->nEntries; 1155ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (n < 2) return TRUE; 1156ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1157ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Curve direction 1158ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov lDescending = cmsIsToneCurveDescending(t); 1159ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1160ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (lDescending) { 1161ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1162ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov last = t ->Table16[0]; 1163ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1164ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i = 1; i < n; i++) { 1165ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1166ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (t ->Table16[i] - last > 2) // We allow some ripple 1167ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1168ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 1169ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov last = t ->Table16[i]; 1170ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1171ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1172ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1173ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else { 1174ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1175ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov last = t ->Table16[n-1]; 1176ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1177ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i = n-2; i >= 0; --i) { 1178ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1179ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (t ->Table16[i] - last > 2) 1180ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return FALSE; 1181ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov else 1182ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov last = t ->Table16[i]; 1183ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1184ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1185ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1186ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1187ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return TRUE; 1188ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1189ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1190ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Same, but for descending tables 1191ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool CMSEXPORT cmsIsToneCurveDescending(const cmsToneCurve* t) 1192ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1193ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 1194ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1195ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return t ->Table16[0] > t ->Table16[t ->nEntries-1]; 1196ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1197ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1198ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1199ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Another info fn: is out gamma table multisegment? 1200ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsBool CMSEXPORT cmsIsToneCurveMultisegment(const cmsToneCurve* t) 1201ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1202ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 1203ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1204ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return t -> nSegments > 1; 1205ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1206ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1207ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(const cmsToneCurve* t) 1208ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1209ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 1210ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1211ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (t -> nSegments != 1) return 0; 1212ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return t ->Segments[0].Type; 1213ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1214ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1215ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// We need accuracy this time 1216ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(const cmsToneCurve* Curve, cmsFloat32Number v) 1217ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1218ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Curve != NULL); 1219ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1220ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Check for 16 bits table. If so, this is a limited-precision tone curve 1221ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Curve ->nSegments == 0) { 1222ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1223ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt16Number In, Out; 1224ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1225ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0); 1226ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Out = cmsEvalToneCurve16(Curve, In); 1227ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1228ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return (cmsFloat32Number) (Out / 65535.0); 1229ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1230ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1231ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return (cmsFloat32Number) EvalSegmentedFn(Curve, v); 1232ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1233ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1234ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// We need xput over here 1235ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsUInt16Number CMSEXPORT cmsEvalToneCurve16(const cmsToneCurve* Curve, cmsUInt16Number v) 1236ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1237ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt16Number out; 1238ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1239ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(Curve != NULL); 1240ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1241ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Curve ->InterpParams ->Interpolation.Lerp16(&v, &out, Curve ->InterpParams); 1242ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return out; 1243ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1244ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1245ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1246ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// Least squares fitting. 1247ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// A mathematical procedure for finding the best-fitting curve to a given set of points by 1248ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve. 1249ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// The sum of the squares of the offsets is used instead of the offset absolute values because 1250ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// this allows the residuals to be treated as a continuous differentiable quantity. 1251ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1252ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// y = f(x) = x ^ g 1253ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1254ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// R = (yi - (xi^g)) 1255ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// R2 = (yi - (xi^g))2 1256ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// SUM R2 = SUM (yi - (xi^g))2 1257ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1258ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// dR2/dg = -2 SUM x^g log(x)(y - x^g) 1259ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// solving for dR2/dg = 0 1260ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// 1261ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov// g = 1/n * SUM(log(y) / log(x)) 1262ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1263ee451cb395940862dad63c85adfe8f2fd55e864cSvet GanovcmsFloat64Number CMSEXPORT cmsEstimateGamma(const cmsToneCurve* t, cmsFloat64Number Precision) 1264ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov{ 1265ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat64Number gamma, sum, sum2; 1266ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsFloat64Number n, x, y, Std; 1267ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov cmsUInt32Number i; 1268ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1269ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov _cmsAssert(t != NULL); 1270ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1271ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov sum = sum2 = n = 0; 1272ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1273ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Excluding endpoints 1274ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) { 1275ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1276ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1); 1277ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov y = (cmsFloat64Number) cmsEvalToneCurveFloat(t, (cmsFloat32Number) x); 1278ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1279ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Avoid 7% on lower part to prevent 1280ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // artifacts due to linear ramps 1281ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1282ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (y > 0. && y < 1. && x > 0.07) { 1283ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1284ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov gamma = log(y) / log(x); 1285ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov sum += gamma; 1286ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov sum2 += gamma * gamma; 1287ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov n++; 1288ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1289ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov } 1290ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1291ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov // Take a look on SD to see if gamma isn't exponential at all 1292ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov Std = sqrt((n * sum2 - sum * sum) / (n*(n-1))); 1293ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1294ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov if (Std > Precision) 1295ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return -1.0; 1296ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov 1297ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov return (sum / n); // The mean 1298ee451cb395940862dad63c85adfe8f2fd55e864cSvet Ganov} 1299