| //--------------------------------------------------------------------------------- |
| // |
| // Little Color Management System |
| // Copyright (c) 1998-2023 Marti Maria Saguer |
| // |
| // Permission is hereby granted, free of charge, to any person obtaining |
| // a copy of this software and associated documentation files (the "Software"), |
| // to deal in the Software without restriction, including without limitation |
| // the rights to use, copy, modify, merge, publish, distribute, sublicense, |
| // and/or sell copies of the Software, and to permit persons to whom the Software |
| // is furnished to do so, subject to the following conditions: |
| // |
| // The above copyright notice and this permission notice shall be included in |
| // all copies or substantial portions of the Software. |
| // |
| // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, |
| // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO |
| // THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND |
| // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE |
| // LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION |
| // OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION |
| // WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| // |
| //--------------------------------------------------------------------------------- |
| // |
| #include "lcms2_internal.h" |
| |
| // Tone curves are powerful constructs that can contain curves specified in diverse ways. |
| // The curve is stored in segments, where each segment can be sampled or specified by parameters. |
| // a 16.bit simplification of the *whole* curve is kept for optimization purposes. For float operation, |
| // each segment is evaluated separately. Plug-ins may be used to define new parametric schemes, |
| // each plug-in may define up to MAX_TYPES_IN_LCMS_PLUGIN functions types. For defining a function, |
| // the plug-in should provide the type id, how many parameters each type has, and a pointer to |
| // a procedure that evaluates the function. In the case of reverse evaluation, the evaluator will |
| // be called with the type id as a negative value, and a sampled version of the reversed curve |
| // will be built. |
| |
| // ----------------------------------------------------------------- Implementation |
| // Maxim number of nodes |
| #define MAX_NODES_IN_CURVE 4097 |
| #define MINUS_INF (-1E22F) |
| #define PLUS_INF (+1E22F) |
| |
| // The list of supported parametric curves |
| typedef struct _cmsParametricCurvesCollection_st { |
| |
| cmsUInt32Number nFunctions; // Number of supported functions in this chunk |
| cmsInt32Number FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types |
| cmsUInt32Number ParameterCount[MAX_TYPES_IN_LCMS_PLUGIN]; // Number of parameters for each function |
| |
| cmsParametricCurveEvaluator Evaluator; // The evaluator |
| |
| struct _cmsParametricCurvesCollection_st* Next; // Next in list |
| |
| } _cmsParametricCurvesCollection; |
| |
| // This is the default (built-in) evaluator |
| static cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R); |
| |
| // The built-in list |
| static const _cmsParametricCurvesCollection DefaultCurves = { |
| 10, // # of curve types |
| { 1, 2, 3, 4, 5, 6, 7, 8, 108, 109 }, // Parametric curve ID |
| { 1, 3, 4, 5, 7, 4, 5, 5, 1, 1 }, // Parameters by type |
| DefaultEvalParametricFn, // Evaluator |
| NULL // Next in chain |
| }; |
| |
| // Duplicates the zone of memory used by the plug-in in the new context |
| static |
| void DupPluginCurvesList(struct _cmsContext_struct* ctx, |
| const struct _cmsContext_struct* src) |
| { |
| _cmsCurvesPluginChunkType newHead = { NULL }; |
| _cmsParametricCurvesCollection* entry; |
| _cmsParametricCurvesCollection* Anterior = NULL; |
| _cmsCurvesPluginChunkType* head = (_cmsCurvesPluginChunkType*) src->chunks[CurvesPlugin]; |
| |
| _cmsAssert(head != NULL); |
| |
| // Walk the list copying all nodes |
| for (entry = head->ParametricCurves; |
| entry != NULL; |
| entry = entry ->Next) { |
| |
| _cmsParametricCurvesCollection *newEntry = ( _cmsParametricCurvesCollection *) _cmsSubAllocDup(ctx ->MemPool, entry, sizeof(_cmsParametricCurvesCollection)); |
| |
| if (newEntry == NULL) |
| return; |
| |
| // We want to keep the linked list order, so this is a little bit tricky |
| newEntry -> Next = NULL; |
| if (Anterior) |
| Anterior -> Next = newEntry; |
| |
| Anterior = newEntry; |
| |
| if (newHead.ParametricCurves == NULL) |
| newHead.ParametricCurves = newEntry; |
| } |
| |
| ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx->MemPool, &newHead, sizeof(_cmsCurvesPluginChunkType)); |
| } |
| |
| // The allocator have to follow the chain |
| void _cmsAllocCurvesPluginChunk(struct _cmsContext_struct* ctx, |
| const struct _cmsContext_struct* src) |
| { |
| _cmsAssert(ctx != NULL); |
| |
| if (src != NULL) { |
| |
| // Copy all linked list |
| DupPluginCurvesList(ctx, src); |
| } |
| else { |
| static _cmsCurvesPluginChunkType CurvesPluginChunk = { NULL }; |
| ctx ->chunks[CurvesPlugin] = _cmsSubAllocDup(ctx ->MemPool, &CurvesPluginChunk, sizeof(_cmsCurvesPluginChunkType)); |
| } |
| } |
| |
| |
| // The linked list head |
| _cmsCurvesPluginChunkType _cmsCurvesPluginChunk = { NULL }; |
| |
| // As a way to install new parametric curves |
| cmsBool _cmsRegisterParametricCurvesPlugin(cmsContext ContextID, cmsPluginBase* Data) |
| { |
| _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin); |
| cmsPluginParametricCurves* Plugin = (cmsPluginParametricCurves*) Data; |
| _cmsParametricCurvesCollection* fl; |
| |
| if (Data == NULL) { |
| |
| ctx -> ParametricCurves = NULL; |
| return TRUE; |
| } |
| |
| fl = (_cmsParametricCurvesCollection*) _cmsPluginMalloc(ContextID, sizeof(_cmsParametricCurvesCollection)); |
| if (fl == NULL) return FALSE; |
| |
| // Copy the parameters |
| fl ->Evaluator = Plugin ->Evaluator; |
| fl ->nFunctions = Plugin ->nFunctions; |
| |
| // Make sure no mem overwrites |
| if (fl ->nFunctions > MAX_TYPES_IN_LCMS_PLUGIN) |
| fl ->nFunctions = MAX_TYPES_IN_LCMS_PLUGIN; |
| |
| // Copy the data |
| memmove(fl->FunctionTypes, Plugin ->FunctionTypes, fl->nFunctions * sizeof(cmsUInt32Number)); |
| memmove(fl->ParameterCount, Plugin ->ParameterCount, fl->nFunctions * sizeof(cmsUInt32Number)); |
| |
| // Keep linked list |
| fl ->Next = ctx->ParametricCurves; |
| ctx->ParametricCurves = fl; |
| |
| // All is ok |
| return TRUE; |
| } |
| |
| |
| // Search in type list, return position or -1 if not found |
| static |
| int IsInSet(int Type, const _cmsParametricCurvesCollection* c) |
| { |
| int i; |
| |
| for (i=0; i < (int) c ->nFunctions; i++) |
| if (abs(Type) == c ->FunctionTypes[i]) return i; |
| |
| return -1; |
| } |
| |
| |
| // Search for the collection which contains a specific type |
| static |
| const _cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index) |
| { |
| const _cmsParametricCurvesCollection* c; |
| int Position; |
| _cmsCurvesPluginChunkType* ctx = ( _cmsCurvesPluginChunkType*) _cmsContextGetClientChunk(ContextID, CurvesPlugin); |
| |
| for (c = ctx->ParametricCurves; c != NULL; c = c ->Next) { |
| |
| Position = IsInSet(Type, c); |
| |
| if (Position != -1) { |
| if (index != NULL) |
| *index = Position; |
| return c; |
| } |
| } |
| // If none found, revert for defaults |
| for (c = &DefaultCurves; c != NULL; c = c ->Next) { |
| |
| Position = IsInSet(Type, c); |
| |
| if (Position != -1) { |
| if (index != NULL) |
| *index = Position; |
| return c; |
| } |
| } |
| |
| return NULL; |
| } |
| |
| // Low level allocate, which takes care of memory details. nEntries may be zero, and in this case |
| // no optimization curve is computed. nSegments may also be zero in the inverse case, where only the |
| // optimization curve is given. Both features simultaneously is an error |
| static |
| cmsToneCurve* AllocateToneCurveStruct(cmsContext ContextID, cmsUInt32Number nEntries, |
| cmsUInt32Number nSegments, const cmsCurveSegment* Segments, |
| const cmsUInt16Number* Values) |
| { |
| cmsToneCurve* p; |
| cmsUInt32Number i; |
| |
| // We allow huge tables, which are then restricted for smoothing operations |
| if (nEntries > 65530) { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve of more than 65530 entries"); |
| return NULL; |
| } |
| |
| if (nEntries == 0 && nSegments == 0) { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "Couldn't create tone curve with zero segments and no table"); |
| return NULL; |
| } |
| |
| // Allocate all required pointers, etc. |
| p = (cmsToneCurve*) _cmsMallocZero(ContextID, sizeof(cmsToneCurve)); |
| if (!p) return NULL; |
| |
| // In this case, there are no segments |
| if (nSegments == 0) { |
| p ->Segments = NULL; |
| p ->Evals = NULL; |
| } |
| else { |
| p ->Segments = (cmsCurveSegment*) _cmsCalloc(ContextID, nSegments, sizeof(cmsCurveSegment)); |
| if (p ->Segments == NULL) goto Error; |
| |
| p ->Evals = (cmsParametricCurveEvaluator*) _cmsCalloc(ContextID, nSegments, sizeof(cmsParametricCurveEvaluator)); |
| if (p ->Evals == NULL) goto Error; |
| } |
| |
| p -> nSegments = nSegments; |
| |
| // This 16-bit table contains a limited precision representation of the whole curve and is kept for |
| // increasing xput on certain operations. |
| if (nEntries == 0) { |
| p ->Table16 = NULL; |
| } |
| else { |
| p ->Table16 = (cmsUInt16Number*) _cmsCalloc(ContextID, nEntries, sizeof(cmsUInt16Number)); |
| if (p ->Table16 == NULL) goto Error; |
| } |
| |
| p -> nEntries = nEntries; |
| |
| // Initialize members if requested |
| if (Values != NULL && (nEntries > 0)) { |
| |
| for (i=0; i < nEntries; i++) |
| p ->Table16[i] = Values[i]; |
| } |
| |
| // Initialize the segments stuff. The evaluator for each segment is located and a pointer to it |
| // is placed in advance to maximize performance. |
| if (Segments != NULL && (nSegments > 0)) { |
| |
| const _cmsParametricCurvesCollection *c; |
| |
| p ->SegInterp = (cmsInterpParams**) _cmsCalloc(ContextID, nSegments, sizeof(cmsInterpParams*)); |
| if (p ->SegInterp == NULL) goto Error; |
| |
| for (i=0; i < nSegments; i++) { |
| |
| // Type 0 is a special marker for table-based curves |
| if (Segments[i].Type == 0) |
| p ->SegInterp[i] = _cmsComputeInterpParams(ContextID, Segments[i].nGridPoints, 1, 1, NULL, CMS_LERP_FLAGS_FLOAT); |
| |
| memmove(&p ->Segments[i], &Segments[i], sizeof(cmsCurveSegment)); |
| |
| if (Segments[i].Type == 0 && Segments[i].SampledPoints != NULL) |
| p ->Segments[i].SampledPoints = (cmsFloat32Number*) _cmsDupMem(ContextID, Segments[i].SampledPoints, sizeof(cmsFloat32Number) * Segments[i].nGridPoints); |
| else |
| p ->Segments[i].SampledPoints = NULL; |
| |
| |
| c = GetParametricCurveByType(ContextID, Segments[i].Type, NULL); |
| if (c != NULL) |
| p ->Evals[i] = c ->Evaluator; |
| } |
| } |
| |
| p ->InterpParams = _cmsComputeInterpParams(ContextID, p ->nEntries, 1, 1, p->Table16, CMS_LERP_FLAGS_16BITS); |
| if (p->InterpParams != NULL) |
| return p; |
| |
| Error: |
| if (p -> SegInterp) _cmsFree(ContextID, p -> SegInterp); |
| if (p -> Segments) _cmsFree(ContextID, p -> Segments); |
| if (p -> Evals) _cmsFree(ContextID, p -> Evals); |
| if (p ->Table16) _cmsFree(ContextID, p ->Table16); |
| _cmsFree(ContextID, p); |
| return NULL; |
| } |
| |
| |
| // Generates a sigmoidal function with desired steepness. |
| cmsINLINE double sigmoid_base(double k, double t) |
| { |
| return (1.0 / (1.0 + exp(-k * t))) - 0.5; |
| } |
| |
| cmsINLINE double inverted_sigmoid_base(double k, double t) |
| { |
| return -log((1.0 / (t + 0.5)) - 1.0) / k; |
| } |
| |
| cmsINLINE double sigmoid_factory(double k, double t) |
| { |
| double correction = 0.5 / sigmoid_base(k, 1); |
| |
| return correction * sigmoid_base(k, 2.0 * t - 1.0) + 0.5; |
| } |
| |
| cmsINLINE double inverse_sigmoid_factory(double k, double t) |
| { |
| double correction = 0.5 / sigmoid_base(k, 1); |
| |
| return (inverted_sigmoid_base(k, (t - 0.5) / correction) + 1.0) / 2.0; |
| } |
| |
| |
| // Parametric Fn using floating point |
| static |
| cmsFloat64Number DefaultEvalParametricFn(cmsInt32Number Type, const cmsFloat64Number Params[], cmsFloat64Number R) |
| { |
| cmsFloat64Number e, Val, disc; |
| |
| switch (Type) { |
| |
| // X = Y ^ Gamma |
| case 1: |
| if (R < 0) { |
| |
| if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) |
| Val = R; |
| else |
| Val = 0; |
| } |
| else |
| Val = pow(R, Params[0]); |
| break; |
| |
| // Type 1 Reversed: X = Y ^1/gamma |
| case -1: |
| if (R < 0) { |
| |
| if (fabs(Params[0] - 1.0) < MATRIX_DET_TOLERANCE) |
| Val = R; |
| else |
| Val = 0; |
| } |
| else |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE) |
| Val = PLUS_INF; |
| else |
| Val = pow(R, 1 / Params[0]); |
| } |
| break; |
| |
| // CIE 122-1966 |
| // Y = (aX + b)^Gamma | X >= -b/a |
| // Y = 0 | else |
| case 2: |
| { |
| |
| if (fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| disc = -Params[2] / Params[1]; |
| |
| if (R >= disc) { |
| |
| e = Params[1] * R + Params[2]; |
| |
| if (e > 0) |
| Val = pow(e, Params[0]); |
| else |
| Val = 0; |
| } |
| else |
| Val = 0; |
| } |
| } |
| break; |
| |
| // Type 2 Reversed |
| // X = (Y ^1/g - b) / a |
| case -2: |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| if (R < 0) |
| Val = 0; |
| else |
| Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1]; |
| |
| if (Val < 0) |
| Val = 0; |
| } |
| } |
| break; |
| |
| |
| // IEC 61966-3 |
| // Y = (aX + b)^Gamma + c | X <= -b/a |
| // Y = c | else |
| case 3: |
| { |
| if (fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| disc = -Params[2] / Params[1]; |
| if (disc < 0) |
| disc = 0; |
| |
| if (R >= disc) { |
| |
| e = Params[1] * R + Params[2]; |
| |
| if (e > 0) |
| Val = pow(e, Params[0]) + Params[3]; |
| else |
| Val = 0; |
| } |
| else |
| Val = Params[3]; |
| } |
| } |
| break; |
| |
| |
| // Type 3 reversed |
| // X=((Y-c)^1/g - b)/a | (Y>=c) |
| // X=-b/a | (Y<c) |
| case -3: |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| if (R >= Params[3]) { |
| |
| e = R - Params[3]; |
| |
| if (e > 0) |
| Val = (pow(e, 1 / Params[0]) - Params[2]) / Params[1]; |
| else |
| Val = 0; |
| } |
| else { |
| Val = -Params[2] / Params[1]; |
| } |
| } |
| } |
| break; |
| |
| |
| // IEC 61966-2.1 (sRGB) |
| // Y = (aX + b)^Gamma | X >= d |
| // Y = cX | X < d |
| case 4: |
| if (R >= Params[4]) { |
| |
| e = Params[1]*R + Params[2]; |
| |
| if (e > 0) |
| Val = pow(e, Params[0]); |
| else |
| Val = 0; |
| } |
| else |
| Val = R * Params[3]; |
| break; |
| |
| // Type 4 reversed |
| // X=((Y^1/g-b)/a) | Y >= (ad+b)^g |
| // X=Y/c | Y< (ad+b)^g |
| case -4: |
| { |
| |
| e = Params[1] * Params[4] + Params[2]; |
| if (e < 0) |
| disc = 0; |
| else |
| disc = pow(e, Params[0]); |
| |
| if (R >= disc) { |
| |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| |
| Val = 0; |
| |
| else |
| Val = (pow(R, 1.0 / Params[0]) - Params[2]) / Params[1]; |
| } |
| else { |
| |
| if (fabs(Params[3]) < MATRIX_DET_TOLERANCE) |
| Val = 0; |
| else |
| Val = R / Params[3]; |
| } |
| |
| } |
| break; |
| |
| |
| // Y = (aX + b)^Gamma + e | X >= d |
| // Y = cX + f | X < d |
| case 5: |
| if (R >= Params[4]) { |
| |
| e = Params[1]*R + Params[2]; |
| |
| if (e > 0) |
| Val = pow(e, Params[0]) + Params[5]; |
| else |
| Val = Params[5]; |
| } |
| else |
| Val = R*Params[3] + Params[6]; |
| break; |
| |
| |
| // Reversed type 5 |
| // X=((Y-e)1/g-b)/a | Y >=(ad+b)^g+e), cd+f |
| // X=(Y-f)/c | else |
| case -5: |
| { |
| disc = Params[3] * Params[4] + Params[6]; |
| if (R >= disc) { |
| |
| e = R - Params[5]; |
| if (e < 0) |
| Val = 0; |
| else |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| |
| Val = 0; |
| else |
| Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1]; |
| } |
| } |
| else { |
| if (fabs(Params[3]) < MATRIX_DET_TOLERANCE) |
| Val = 0; |
| else |
| Val = (R - Params[6]) / Params[3]; |
| } |
| |
| } |
| break; |
| |
| |
| // Types 6,7,8 comes from segmented curves as described in ICCSpecRevision_02_11_06_Float.pdf |
| // Type 6 is basically identical to type 5 without d |
| |
| // Y = (a * X + b) ^ Gamma + c |
| case 6: |
| e = Params[1]*R + Params[2]; |
| |
| if (e < 0) |
| Val = Params[3]; |
| else |
| Val = pow(e, Params[0]) + Params[3]; |
| break; |
| |
| // ((Y - c) ^1/Gamma - b) / a |
| case -6: |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| e = R - Params[3]; |
| if (e < 0) |
| Val = 0; |
| else |
| Val = (pow(e, 1.0 / Params[0]) - Params[2]) / Params[1]; |
| } |
| } |
| break; |
| |
| |
| // Y = a * log (b * X^Gamma + c) + d |
| case 7: |
| |
| e = Params[2] * pow(R, Params[0]) + Params[3]; |
| if (e <= 0) |
| Val = Params[4]; |
| else |
| Val = Params[1]*log10(e) + Params[4]; |
| break; |
| |
| // (Y - d) / a = log(b * X ^Gamma + c) |
| // pow(10, (Y-d) / a) = b * X ^Gamma + c |
| // pow((pow(10, (Y-d) / a) - c) / b, 1/g) = X |
| case -7: |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[1]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[2]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| Val = pow((pow(10.0, (R - Params[4]) / Params[1]) - Params[3]) / Params[2], 1.0 / Params[0]); |
| } |
| } |
| break; |
| |
| |
| //Y = a * b^(c*X+d) + e |
| case 8: |
| Val = (Params[0] * pow(Params[1], Params[2] * R + Params[3]) + Params[4]); |
| break; |
| |
| |
| // Y = (log((y-e) / a) / log(b) - d ) / c |
| // a=0, b=1, c=2, d=3, e=4, |
| case -8: |
| |
| disc = R - Params[4]; |
| if (disc < 0) Val = 0; |
| else |
| { |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE || |
| fabs(Params[2]) < MATRIX_DET_TOLERANCE) |
| { |
| Val = 0; |
| } |
| else |
| { |
| Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2]; |
| } |
| } |
| break; |
| |
| |
| // S-Shaped: (1 - (1-x)^1/g)^1/g |
| case 108: |
| if (fabs(Params[0]) < MATRIX_DET_TOLERANCE) |
| Val = 0; |
| else |
| Val = pow(1.0 - pow(1 - R, 1/Params[0]), 1/Params[0]); |
| break; |
| |
| // y = (1 - (1-x)^1/g)^1/g |
| // y^g = (1 - (1-x)^1/g) |
| // 1 - y^g = (1-x)^1/g |
| // (1 - y^g)^g = 1 - x |
| // 1 - (1 - y^g)^g |
| case -108: |
| Val = 1 - pow(1 - pow(R, Params[0]), Params[0]); |
| break; |
| |
| // Sigmoidals |
| case 109: |
| Val = sigmoid_factory(Params[0], R); |
| break; |
| |
| case -109: |
| Val = inverse_sigmoid_factory(Params[0], R); |
| break; |
| |
| default: |
| // Unsupported parametric curve. Should never reach here |
| return 0; |
| } |
| |
| return Val; |
| } |
| |
| // Evaluate a segmented function for a single value. Return -Inf if no valid segment found . |
| // If fn type is 0, perform an interpolation on the table |
| static |
| cmsFloat64Number EvalSegmentedFn(const cmsToneCurve *g, cmsFloat64Number R) |
| { |
| int i; |
| cmsFloat32Number Out32; |
| cmsFloat64Number Out; |
| |
| for (i = (int) g->nSegments - 1; i >= 0; --i) { |
| |
| // Check for domain |
| if ((R > g->Segments[i].x0) && (R <= g->Segments[i].x1)) { |
| |
| // Type == 0 means segment is sampled |
| if (g->Segments[i].Type == 0) { |
| |
| cmsFloat32Number R1 = (cmsFloat32Number)(R - g->Segments[i].x0) / (g->Segments[i].x1 - g->Segments[i].x0); |
| |
| // Setup the table (TODO: clean that) |
| g->SegInterp[i]->Table = g->Segments[i].SampledPoints; |
| |
| g->SegInterp[i]->Interpolation.LerpFloat(&R1, &Out32, g->SegInterp[i]); |
| Out = (cmsFloat64Number) Out32; |
| |
| } |
| else { |
| Out = g->Evals[i](g->Segments[i].Type, g->Segments[i].Params, R); |
| } |
| |
| if (isinf(Out)) |
| return PLUS_INF; |
| else |
| { |
| if (isinf(-Out)) |
| return MINUS_INF; |
| } |
| |
| return Out; |
| } |
| } |
| |
| return MINUS_INF; |
| } |
| |
| // Access to estimated low-res table |
| cmsUInt32Number CMSEXPORT cmsGetToneCurveEstimatedTableEntries(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| return t ->nEntries; |
| } |
| |
| const cmsUInt16Number* CMSEXPORT cmsGetToneCurveEstimatedTable(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| return t ->Table16; |
| } |
| |
| |
| // Create an empty gamma curve, by using tables. This specifies only the limited-precision part, and leaves the |
| // floating point description empty. |
| cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurve16(cmsContext ContextID, cmsUInt32Number nEntries, const cmsUInt16Number Values[]) |
| { |
| return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values); |
| } |
| |
| static |
| cmsUInt32Number EntriesByGamma(cmsFloat64Number Gamma) |
| { |
| if (fabs(Gamma - 1.0) < 0.001) return 2; |
| return 4096; |
| } |
| |
| |
| // Create a segmented gamma, fill the table |
| cmsToneCurve* CMSEXPORT cmsBuildSegmentedToneCurve(cmsContext ContextID, |
| cmsUInt32Number nSegments, const cmsCurveSegment Segments[]) |
| { |
| cmsUInt32Number i; |
| cmsFloat64Number R, Val; |
| cmsToneCurve* g; |
| cmsUInt32Number nGridPoints = 4096; |
| |
| _cmsAssert(Segments != NULL); |
| |
| // Optimizatin for identity curves. |
| if (nSegments == 1 && Segments[0].Type == 1) { |
| |
| nGridPoints = EntriesByGamma(Segments[0].Params[0]); |
| } |
| |
| g = AllocateToneCurveStruct(ContextID, nGridPoints, nSegments, Segments, NULL); |
| if (g == NULL) return NULL; |
| |
| // Once we have the floating point version, we can approximate a 16 bit table of 4096 entries |
| // for performance reasons. This table would normally not be used except on 8/16 bits transforms. |
| for (i = 0; i < nGridPoints; i++) { |
| |
| R = (cmsFloat64Number) i / (nGridPoints-1); |
| |
| Val = EvalSegmentedFn(g, R); |
| |
| // Round and saturate |
| g ->Table16[i] = _cmsQuickSaturateWord(Val * 65535.0); |
| } |
| |
| return g; |
| } |
| |
| // Use a segmented curve to store the floating point table |
| cmsToneCurve* CMSEXPORT cmsBuildTabulatedToneCurveFloat(cmsContext ContextID, cmsUInt32Number nEntries, const cmsFloat32Number values[]) |
| { |
| cmsCurveSegment Seg[3]; |
| |
| // Do some housekeeping |
| if (nEntries == 0 || values == NULL) |
| return NULL; |
| |
| // A segmented tone curve should have function segments in the first and last positions |
| // Initialize segmented curve part up to 0 to constant value = samples[0] |
| Seg[0].x0 = MINUS_INF; |
| Seg[0].x1 = 0; |
| Seg[0].Type = 6; |
| |
| Seg[0].Params[0] = 1; |
| Seg[0].Params[1] = 0; |
| Seg[0].Params[2] = 0; |
| Seg[0].Params[3] = values[0]; |
| Seg[0].Params[4] = 0; |
| |
| // From zero to 1 |
| Seg[1].x0 = 0; |
| Seg[1].x1 = 1.0; |
| Seg[1].Type = 0; |
| |
| Seg[1].nGridPoints = nEntries; |
| Seg[1].SampledPoints = (cmsFloat32Number*) values; |
| |
| // Final segment is constant = lastsample |
| Seg[2].x0 = 1.0; |
| Seg[2].x1 = PLUS_INF; |
| Seg[2].Type = 6; |
| |
| Seg[2].Params[0] = 1; |
| Seg[2].Params[1] = 0; |
| Seg[2].Params[2] = 0; |
| Seg[2].Params[3] = values[nEntries-1]; |
| Seg[2].Params[4] = 0; |
| |
| |
| return cmsBuildSegmentedToneCurve(ContextID, 3, Seg); |
| } |
| |
| // Parametric curves |
| // |
| // Parameters goes as: Curve, a, b, c, d, e, f |
| // Type is the ICC type +1 |
| // if type is negative, then the curve is analytically inverted |
| cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[]) |
| { |
| cmsCurveSegment Seg0; |
| int Pos = 0; |
| cmsUInt32Number size; |
| const _cmsParametricCurvesCollection* c = GetParametricCurveByType(ContextID, Type, &Pos); |
| |
| _cmsAssert(Params != NULL); |
| |
| if (c == NULL) { |
| cmsSignalError(ContextID, cmsERROR_UNKNOWN_EXTENSION, "Invalid parametric curve type %d", Type); |
| return NULL; |
| } |
| |
| memset(&Seg0, 0, sizeof(Seg0)); |
| |
| Seg0.x0 = MINUS_INF; |
| Seg0.x1 = PLUS_INF; |
| Seg0.Type = Type; |
| |
| size = c->ParameterCount[Pos] * sizeof(cmsFloat64Number); |
| memmove(Seg0.Params, Params, size); |
| |
| return cmsBuildSegmentedToneCurve(ContextID, 1, &Seg0); |
| } |
| |
| |
| |
| // Build a gamma table based on gamma constant |
| cmsToneCurve* CMSEXPORT cmsBuildGamma(cmsContext ContextID, cmsFloat64Number Gamma) |
| { |
| return cmsBuildParametricToneCurve(ContextID, 1, &Gamma); |
| } |
| |
| |
| // Free all memory taken by the gamma curve |
| void CMSEXPORT cmsFreeToneCurve(cmsToneCurve* Curve) |
| { |
| cmsContext ContextID; |
| |
| // added by Xiaochuan Liu |
| // Curve->InterpParams may be null |
| if (Curve == NULL || Curve->InterpParams == NULL) return; |
| |
| ContextID = Curve ->InterpParams->ContextID; |
| |
| _cmsFreeInterpParams(Curve ->InterpParams); |
| Curve ->InterpParams = NULL; |
| |
| if (Curve -> Table16) { |
| _cmsFree(ContextID, Curve ->Table16); |
| Curve ->Table16 = NULL; |
| } |
| |
| if (Curve ->Segments) { |
| |
| cmsUInt32Number i; |
| |
| for (i=0; i < Curve ->nSegments; i++) { |
| |
| if (Curve ->Segments[i].SampledPoints) { |
| _cmsFree(ContextID, Curve ->Segments[i].SampledPoints); |
| Curve ->Segments[i].SampledPoints = NULL; |
| } |
| |
| if (Curve ->SegInterp[i] != 0) { |
| _cmsFreeInterpParams(Curve->SegInterp[i]); |
| Curve->SegInterp[i] = NULL; |
| } |
| } |
| |
| _cmsFree(ContextID, Curve ->Segments); |
| Curve ->Segments = NULL; |
| _cmsFree(ContextID, Curve ->SegInterp); |
| Curve ->SegInterp = NULL; |
| } |
| |
| if (Curve -> Evals) { |
| _cmsFree(ContextID, Curve -> Evals); |
| Curve -> Evals = NULL; |
| } |
| |
| _cmsFree(ContextID, Curve); |
| } |
| |
| // Utility function, free 3 gamma tables |
| void CMSEXPORT cmsFreeToneCurveTriple(cmsToneCurve* Curve[3]) |
| { |
| |
| _cmsAssert(Curve != NULL); |
| |
| if (Curve[0] != NULL) cmsFreeToneCurve(Curve[0]); |
| if (Curve[1] != NULL) cmsFreeToneCurve(Curve[1]); |
| if (Curve[2] != NULL) cmsFreeToneCurve(Curve[2]); |
| |
| Curve[0] = Curve[1] = Curve[2] = NULL; |
| } |
| |
| |
| // Duplicate a gamma table |
| cmsToneCurve* CMSEXPORT cmsDupToneCurve(const cmsToneCurve* In) |
| { |
| if (In == NULL) return NULL; |
| |
| return AllocateToneCurveStruct(In ->InterpParams ->ContextID, In ->nEntries, In ->nSegments, In ->Segments, In ->Table16); |
| } |
| |
| // Joins two curves for X and Y. Curves should be monotonic. |
| // We want to get |
| // |
| // y = Y^-1(X(t)) |
| // |
| cmsToneCurve* CMSEXPORT cmsJoinToneCurve(cmsContext ContextID, |
| const cmsToneCurve* X, |
| const cmsToneCurve* Y, cmsUInt32Number nResultingPoints) |
| { |
| cmsToneCurve* out = NULL; |
| cmsToneCurve* Yreversed = NULL; |
| cmsFloat32Number t, x; |
| cmsFloat32Number* Res = NULL; |
| cmsUInt32Number i; |
| |
| |
| _cmsAssert(X != NULL); |
| _cmsAssert(Y != NULL); |
| |
| Yreversed = cmsReverseToneCurveEx(nResultingPoints, Y); |
| if (Yreversed == NULL) goto Error; |
| |
| Res = (cmsFloat32Number*) _cmsCalloc(ContextID, nResultingPoints, sizeof(cmsFloat32Number)); |
| if (Res == NULL) goto Error; |
| |
| //Iterate |
| for (i=0; i < nResultingPoints; i++) { |
| |
| t = (cmsFloat32Number) i / (cmsFloat32Number)(nResultingPoints-1); |
| x = cmsEvalToneCurveFloat(X, t); |
| Res[i] = cmsEvalToneCurveFloat(Yreversed, x); |
| } |
| |
| // Allocate space for output |
| out = cmsBuildTabulatedToneCurveFloat(ContextID, nResultingPoints, Res); |
| |
| Error: |
| |
| if (Res != NULL) _cmsFree(ContextID, Res); |
| if (Yreversed != NULL) cmsFreeToneCurve(Yreversed); |
| |
| return out; |
| } |
| |
| |
| |
| // Get the surrounding nodes. This is tricky on non-monotonic tables |
| static |
| int GetInterval(cmsFloat64Number In, const cmsUInt16Number LutTable[], const struct _cms_interp_struc* p) |
| { |
| int i; |
| int y0, y1; |
| |
| // A 1 point table is not allowed |
| if (p -> Domain[0] < 1) return -1; |
| |
| // Let's see if ascending or descending. |
| if (LutTable[0] < LutTable[p ->Domain[0]]) { |
| |
| // Table is overall ascending |
| for (i = (int) p->Domain[0] - 1; i >= 0; --i) { |
| |
| y0 = LutTable[i]; |
| y1 = LutTable[i+1]; |
| |
| if (y0 <= y1) { // Increasing |
| if (In >= y0 && In <= y1) return i; |
| } |
| else |
| if (y1 < y0) { // Decreasing |
| if (In >= y1 && In <= y0) return i; |
| } |
| } |
| } |
| else { |
| // Table is overall descending |
| for (i=0; i < (int) p -> Domain[0]; i++) { |
| |
| y0 = LutTable[i]; |
| y1 = LutTable[i+1]; |
| |
| if (y0 <= y1) { // Increasing |
| if (In >= y0 && In <= y1) return i; |
| } |
| else |
| if (y1 < y0) { // Decreasing |
| if (In >= y1 && In <= y0) return i; |
| } |
| } |
| } |
| |
| return -1; |
| } |
| |
| // Reverse a gamma table |
| cmsToneCurve* CMSEXPORT cmsReverseToneCurveEx(cmsUInt32Number nResultSamples, const cmsToneCurve* InCurve) |
| { |
| cmsToneCurve *out; |
| cmsFloat64Number a = 0, b = 0, y, x1, y1, x2, y2; |
| int i, j; |
| int Ascending; |
| |
| _cmsAssert(InCurve != NULL); |
| |
| // Try to reverse it analytically whatever possible |
| |
| if (InCurve ->nSegments == 1 && InCurve ->Segments[0].Type > 0 && |
| /* InCurve -> Segments[0].Type <= 5 */ |
| GetParametricCurveByType(InCurve ->InterpParams->ContextID, InCurve ->Segments[0].Type, NULL) != NULL) { |
| |
| return cmsBuildParametricToneCurve(InCurve ->InterpParams->ContextID, |
| -(InCurve -> Segments[0].Type), |
| InCurve -> Segments[0].Params); |
| } |
| |
| // Nope, reverse the table. |
| out = cmsBuildTabulatedToneCurve16(InCurve ->InterpParams->ContextID, nResultSamples, NULL); |
| if (out == NULL) |
| return NULL; |
| |
| // We want to know if this is an ascending or descending table |
| Ascending = !cmsIsToneCurveDescending(InCurve); |
| |
| // Iterate across Y axis |
| for (i=0; i < (int) nResultSamples; i++) { |
| |
| y = (cmsFloat64Number) i * 65535.0 / (nResultSamples - 1); |
| |
| // Find interval in which y is within. |
| j = GetInterval(y, InCurve->Table16, InCurve->InterpParams); |
| if (j >= 0) { |
| |
| |
| // Get limits of interval |
| x1 = InCurve ->Table16[j]; |
| x2 = InCurve ->Table16[j+1]; |
| |
| y1 = (cmsFloat64Number) (j * 65535.0) / (InCurve ->nEntries - 1); |
| y2 = (cmsFloat64Number) ((j+1) * 65535.0 ) / (InCurve ->nEntries - 1); |
| |
| // If collapsed, then use any |
| if (x1 == x2) { |
| |
| out ->Table16[i] = _cmsQuickSaturateWord(Ascending ? y2 : y1); |
| continue; |
| |
| } else { |
| |
| // Interpolate |
| a = (y2 - y1) / (x2 - x1); |
| b = y2 - a * x2; |
| } |
| } |
| |
| out ->Table16[i] = _cmsQuickSaturateWord(a* y + b); |
| } |
| |
| |
| return out; |
| } |
| |
| // Reverse a gamma table |
| cmsToneCurve* CMSEXPORT cmsReverseToneCurve(const cmsToneCurve* InGamma) |
| { |
| _cmsAssert(InGamma != NULL); |
| |
| return cmsReverseToneCurveEx(4096, InGamma); |
| } |
| |
| // From: Eilers, P.H.C. (1994) Smoothing and interpolation with finite |
| // differences. in: Graphic Gems IV, Heckbert, P.S. (ed.), Academic press. |
| // |
| // Smoothing and interpolation with second differences. |
| // |
| // Input: weights (w), data (y): vector from 1 to m. |
| // Input: smoothing parameter (lambda), length (m). |
| // Output: smoothed vector (z): vector from 1 to m. |
| |
| static |
| cmsBool smooth2(cmsContext ContextID, cmsFloat32Number w[], cmsFloat32Number y[], |
| cmsFloat32Number z[], cmsFloat32Number lambda, int m) |
| { |
| int i, i1, i2; |
| cmsFloat32Number *c, *d, *e; |
| cmsBool st; |
| |
| |
| c = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); |
| d = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); |
| e = (cmsFloat32Number*) _cmsCalloc(ContextID, MAX_NODES_IN_CURVE, sizeof(cmsFloat32Number)); |
| |
| if (c != NULL && d != NULL && e != NULL) { |
| |
| |
| d[1] = w[1] + lambda; |
| c[1] = -2 * lambda / d[1]; |
| e[1] = lambda /d[1]; |
| z[1] = w[1] * y[1]; |
| d[2] = w[2] + 5 * lambda - d[1] * c[1] * c[1]; |
| c[2] = (-4 * lambda - d[1] * c[1] * e[1]) / d[2]; |
| e[2] = lambda / d[2]; |
| z[2] = w[2] * y[2] - c[1] * z[1]; |
| |
| for (i = 3; i < m - 1; i++) { |
| i1 = i - 1; i2 = i - 2; |
| d[i]= w[i] + 6 * lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; |
| c[i] = (-4 * lambda -d[i1] * c[i1] * e[i1])/ d[i]; |
| e[i] = lambda / d[i]; |
| z[i] = w[i] * y[i] - c[i1] * z[i1] - e[i2] * z[i2]; |
| } |
| |
| i1 = m - 2; i2 = m - 3; |
| |
| d[m - 1] = w[m - 1] + 5 * lambda -c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; |
| c[m - 1] = (-2 * lambda - d[i1] * c[i1] * e[i1]) / d[m - 1]; |
| z[m - 1] = w[m - 1] * y[m - 1] - c[i1] * z[i1] - e[i2] * z[i2]; |
| i1 = m - 1; i2 = m - 2; |
| |
| d[m] = w[m] + lambda - c[i1] * c[i1] * d[i1] - e[i2] * e[i2] * d[i2]; |
| z[m] = (w[m] * y[m] - c[i1] * z[i1] - e[i2] * z[i2]) / d[m]; |
| z[m - 1] = z[m - 1] / d[m - 1] - c[m - 1] * z[m]; |
| |
| for (i = m - 2; 1<= i; i--) |
| z[i] = z[i] / d[i] - c[i] * z[i + 1] - e[i] * z[i + 2]; |
| |
| st = TRUE; |
| } |
| else st = FALSE; |
| |
| if (c != NULL) _cmsFree(ContextID, c); |
| if (d != NULL) _cmsFree(ContextID, d); |
| if (e != NULL) _cmsFree(ContextID, e); |
| |
| return st; |
| } |
| |
| // Smooths a curve sampled at regular intervals. |
| cmsBool CMSEXPORT cmsSmoothToneCurve(cmsToneCurve* Tab, cmsFloat64Number lambda) |
| { |
| cmsBool SuccessStatus = TRUE; |
| cmsFloat32Number *w, *y, *z; |
| cmsUInt32Number i, nItems, Zeros, Poles; |
| cmsBool notCheck = FALSE; |
| |
| if (Tab != NULL && Tab->InterpParams != NULL) |
| { |
| cmsContext ContextID = Tab->InterpParams->ContextID; |
| |
| if (!cmsIsToneCurveLinear(Tab)) // Only non-linear curves need smoothing |
| { |
| nItems = Tab->nEntries; |
| if (nItems < MAX_NODES_IN_CURVE) |
| { |
| // Allocate one more item than needed |
| w = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number)); |
| y = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number)); |
| z = (cmsFloat32Number *)_cmsCalloc(ContextID, nItems + 1, sizeof(cmsFloat32Number)); |
| |
| if (w != NULL && y != NULL && z != NULL) // Ensure no memory allocation failure |
| { |
| memset(w, 0, (nItems + 1) * sizeof(cmsFloat32Number)); |
| memset(y, 0, (nItems + 1) * sizeof(cmsFloat32Number)); |
| memset(z, 0, (nItems + 1) * sizeof(cmsFloat32Number)); |
| |
| for (i = 0; i < nItems; i++) |
| { |
| y[i + 1] = (cmsFloat32Number)Tab->Table16[i]; |
| w[i + 1] = 1.0; |
| } |
| |
| if (lambda < 0) |
| { |
| notCheck = TRUE; |
| lambda = -lambda; |
| } |
| |
| if (smooth2(ContextID, w, y, z, (cmsFloat32Number)lambda, (int)nItems)) |
| { |
| // Do some reality - checking... |
| |
| Zeros = Poles = 0; |
| for (i = nItems; i > 1; --i) |
| { |
| if (z[i] == 0.) Zeros++; |
| if (z[i] >= 65535.) Poles++; |
| if (z[i] < z[i - 1]) |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Non-Monotonic."); |
| SuccessStatus = notCheck; |
| break; |
| } |
| } |
| |
| if (SuccessStatus && Zeros > (nItems / 3)) |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly zeros."); |
| SuccessStatus = notCheck; |
| } |
| |
| if (SuccessStatus && Poles > (nItems / 3)) |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Degenerated, mostly poles."); |
| SuccessStatus = notCheck; |
| } |
| |
| if (SuccessStatus) // Seems ok |
| { |
| for (i = 0; i < nItems; i++) |
| { |
| // Clamp to cmsUInt16Number |
| Tab->Table16[i] = _cmsQuickSaturateWord(z[i + 1]); |
| } |
| } |
| } |
| else // Could not smooth |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Function smooth2 failed."); |
| SuccessStatus = FALSE; |
| } |
| } |
| else // One or more buffers could not be allocated |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Could not allocate memory."); |
| SuccessStatus = FALSE; |
| } |
| |
| if (z != NULL) |
| _cmsFree(ContextID, z); |
| |
| if (y != NULL) |
| _cmsFree(ContextID, y); |
| |
| if (w != NULL) |
| _cmsFree(ContextID, w); |
| } |
| else // too many items in the table |
| { |
| cmsSignalError(ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: Too many points."); |
| SuccessStatus = FALSE; |
| } |
| } |
| } |
| else // Tab parameter or Tab->InterpParams is NULL |
| { |
| // Can't signal an error here since the ContextID is not known at this point |
| SuccessStatus = FALSE; |
| } |
| |
| return SuccessStatus; |
| } |
| |
| // Is a table linear? Do not use parametric since we cannot guarantee some weird parameters resulting |
| // in a linear table. This way assures it is linear in 12 bits, which should be enough in most cases. |
| cmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve) |
| { |
| int i; |
| int diff; |
| |
| _cmsAssert(Curve != NULL); |
| |
| for (i=0; i < (int) Curve ->nEntries; i++) { |
| |
| diff = abs((int) Curve->Table16[i] - (int) _cmsQuantizeVal(i, Curve ->nEntries)); |
| if (diff > 0x0f) |
| return FALSE; |
| } |
| |
| return TRUE; |
| } |
| |
| // Same, but for monotonicity |
| cmsBool CMSEXPORT cmsIsToneCurveMonotonic(const cmsToneCurve* t) |
| { |
| cmsUInt32Number n; |
| int i, last; |
| cmsBool lDescending; |
| |
| _cmsAssert(t != NULL); |
| |
| // Degenerated curves are monotonic? Ok, let's pass them |
| n = t ->nEntries; |
| if (n < 2) return TRUE; |
| |
| // Curve direction |
| lDescending = cmsIsToneCurveDescending(t); |
| |
| if (lDescending) { |
| |
| last = t ->Table16[0]; |
| |
| for (i = 1; i < (int) n; i++) { |
| |
| if (t ->Table16[i] - last > 2) // We allow some ripple |
| return FALSE; |
| else |
| last = t ->Table16[i]; |
| |
| } |
| } |
| else { |
| |
| last = t ->Table16[n-1]; |
| |
| for (i = (int) n - 2; i >= 0; --i) { |
| |
| if (t ->Table16[i] - last > 2) |
| return FALSE; |
| else |
| last = t ->Table16[i]; |
| |
| } |
| } |
| |
| return TRUE; |
| } |
| |
| // Same, but for descending tables |
| cmsBool CMSEXPORT cmsIsToneCurveDescending(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| |
| return t ->Table16[0] > t ->Table16[t ->nEntries-1]; |
| } |
| |
| |
| // Another info fn: is out gamma table multisegment? |
| cmsBool CMSEXPORT cmsIsToneCurveMultisegment(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| |
| return t -> nSegments > 1; |
| } |
| |
| cmsInt32Number CMSEXPORT cmsGetToneCurveParametricType(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| |
| if (t -> nSegments != 1) return 0; |
| return t ->Segments[0].Type; |
| } |
| |
| // We need accuracy this time |
| cmsFloat32Number CMSEXPORT cmsEvalToneCurveFloat(const cmsToneCurve* Curve, cmsFloat32Number v) |
| { |
| _cmsAssert(Curve != NULL); |
| |
| // Check for 16 bits table. If so, this is a limited-precision tone curve |
| if (Curve ->nSegments == 0) { |
| |
| cmsUInt16Number In, Out; |
| |
| In = (cmsUInt16Number) _cmsQuickSaturateWord(v * 65535.0); |
| Out = cmsEvalToneCurve16(Curve, In); |
| |
| return (cmsFloat32Number) (Out / 65535.0); |
| } |
| |
| return (cmsFloat32Number) EvalSegmentedFn(Curve, v); |
| } |
| |
| // We need xput over here |
| cmsUInt16Number CMSEXPORT cmsEvalToneCurve16(const cmsToneCurve* Curve, cmsUInt16Number v) |
| { |
| cmsUInt16Number out; |
| |
| _cmsAssert(Curve != NULL); |
| |
| Curve ->InterpParams ->Interpolation.Lerp16(&v, &out, Curve ->InterpParams); |
| return out; |
| } |
| |
| |
| // Least squares fitting. |
| // A mathematical procedure for finding the best-fitting curve to a given set of points by |
| // minimizing the sum of the squares of the offsets ("the residuals") of the points from the curve. |
| // The sum of the squares of the offsets is used instead of the offset absolute values because |
| // this allows the residuals to be treated as a continuous differentiable quantity. |
| // |
| // y = f(x) = x ^ g |
| // |
| // R = (yi - (xi^g)) |
| // R2 = (yi - (xi^g))2 |
| // SUM R2 = SUM (yi - (xi^g))2 |
| // |
| // dR2/dg = -2 SUM x^g log(x)(y - x^g) |
| // solving for dR2/dg = 0 |
| // |
| // g = 1/n * SUM(log(y) / log(x)) |
| |
| cmsFloat64Number CMSEXPORT cmsEstimateGamma(const cmsToneCurve* t, cmsFloat64Number Precision) |
| { |
| cmsFloat64Number gamma, sum, sum2; |
| cmsFloat64Number n, x, y, Std; |
| cmsUInt32Number i; |
| |
| _cmsAssert(t != NULL); |
| |
| sum = sum2 = n = 0; |
| |
| // Excluding endpoints |
| for (i=1; i < (MAX_NODES_IN_CURVE-1); i++) { |
| |
| x = (cmsFloat64Number) i / (MAX_NODES_IN_CURVE-1); |
| y = (cmsFloat64Number) cmsEvalToneCurveFloat(t, (cmsFloat32Number) x); |
| |
| // Avoid 7% on lower part to prevent |
| // artifacts due to linear ramps |
| |
| if (y > 0. && y < 1. && x > 0.07) { |
| |
| gamma = log(y) / log(x); |
| sum += gamma; |
| sum2 += gamma * gamma; |
| n++; |
| } |
| } |
| |
| // We need enough valid samples |
| if (n <= 1) return -1.0; |
| |
| // Take a look on SD to see if gamma isn't exponential at all |
| Std = sqrt((n * sum2 - sum * sum) / (n*(n-1))); |
| |
| if (Std > Precision) |
| return -1.0; |
| |
| return (sum / n); // The mean |
| } |
| |
| |
| // Retrieve parameters on one-segment tone curves |
| |
| cmsFloat64Number* CMSEXPORT cmsGetToneCurveParams(const cmsToneCurve* t) |
| { |
| _cmsAssert(t != NULL); |
| |
| if (t->nSegments != 1) return NULL; |
| return t->Segments[0].Params; |
| } |
