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Java example source code file (cmsgamma.c)
The cmsgamma.c Java example source code/* * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. Oracle designates this * particular file as subject to the "Classpath" exception as provided * by Oracle in the LICENSE file that accompanied this code. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. */ // This file is available under and governed by the GNU General Public // License version 2 only, as published by the Free Software Foundation. // However, the following notice accompanied the original version of this // file: // //--------------------------------------------------------------------------------- // // Little Color Management System // Copyright (c) 1998-2012 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 { int nFunctions; // Number of supported functions in this chunk int FunctionTypes[MAX_TYPES_IN_LCMS_PLUGIN]; // The identification types int 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 _cmsParametricCurvesCollection DefaultCurves = { 9, // # of curve types { 1, 2, 3, 4, 5, 6, 7, 8, 108 }, // Parametric curve ID { 1, 3, 4, 5, 7, 4, 5, 5, 1 }, // Parameters by type DefaultEvalParametricFn, // Evaluator NULL // Next in chain }; // The linked list head static _cmsParametricCurvesCollection* ParametricCurves = &DefaultCurves; // As a way to install new parametric curves cmsBool _cmsRegisterParametricCurvesPlugin(cmsPluginBase* Data) { cmsPluginParametricCurves* Plugin = (cmsPluginParametricCurves*) Data; _cmsParametricCurvesCollection* fl; if (Data == NULL) { ParametricCurves = &DefaultCurves; return TRUE; } fl = (_cmsParametricCurvesCollection*) _cmsPluginMalloc(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 = ParametricCurves; ParametricCurves = fl; // All is ok return TRUE; } // Search in type list, return position or -1 if not found static int IsInSet(int Type, _cmsParametricCurvesCollection* c) { int i; for (i=0; i < c ->nFunctions; i++) if (abs(Type) == c ->FunctionTypes[i]) return i; return -1; } // Search for the collection which contains a specific type static _cmsParametricCurvesCollection *GetParametricCurveByType(int Type, int* index) { _cmsParametricCurvesCollection* c; int Position; for (c = ParametricCurves; 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 optimation 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, cmsInt32Number nEntries, cmsInt32Number nSegments, const cmsCurveSegment* Segments, const cmsUInt16Number* Values) { cmsToneCurve* p; int i; // We allow huge tables, which are then restricted for smoothing operations if (nEntries > 65530 || nEntries < 0) { 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)) { _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(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); return p; Error: 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; } // 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 Val = pow(R, 1/Params[0]); break; // CIE 122-1966 // Y = (aX + b)^Gamma | X >= -b/a // Y = 0 | else case 2: 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 (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 | X <= -b/a // Y = c | else case 3: 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 (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) { Val = (pow(R, 1.0/Params[0]) - Params[2]) / Params[1]; } 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 = 0; } 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 Val = (pow(e, 1.0/Params[0]) - Params[2]) / Params[1]; } 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 = 0; else Val = pow(e, Params[0]) + Params[3]; break; // ((Y - c) ^1/Gamma - b) / a case -6: 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 = 0; 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: 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 Val = (log(disc / Params[0]) / log(Params[1]) - Params[3]) / Params[2]; break; // S-Shaped: (1 - (1-x)^1/g)^1/g case 108: 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; default: // Unsupported parametric curve. Should never reach here return 0; } return Val; } // Evaluate a segmented funtion for a single value. Return -1 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; for (i = 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); cmsFloat32Number Out; // Setup the table (TODO: clean that) g ->SegInterp[i]-> Table = g ->Segments[i].SampledPoints; g ->SegInterp[i] -> Interpolation.LerpFloat(&R1, &Out, g ->SegInterp[i]); return Out; } else return g ->Evals[i](g->Segments[i].Type, g ->Segments[i].Params, R); } } 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, cmsInt32Number nEntries, const cmsUInt16Number Values[]) { return AllocateToneCurveStruct(ContextID, nEntries, 0, NULL, Values); } static int 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, cmsInt32Number nSegments, const cmsCurveSegment Segments[]) { int i; cmsFloat64Number R, Val; cmsToneCurve* g; int 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[2]; // Initialize segmented curve part up to 0 Seg[0].x0 = -1; 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] = 0; Seg[0].Params[4] = 0; // From zero to any Seg[1].x0 = 0; Seg[1].x1 = 1.0; Seg[1].Type = 0; Seg[1].nGridPoints = nEntries; Seg[1].SampledPoints = (cmsFloat32Number*) values; return cmsBuildSegmentedToneCurve(ContextID, 2, 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 analyticaly inverted cmsToneCurve* CMSEXPORT cmsBuildParametricToneCurve(cmsContext ContextID, cmsInt32Number Type, const cmsFloat64Number Params[]) { cmsCurveSegment Seg0; int Pos = 0; cmsUInt32Number size; _cmsParametricCurvesCollection* c = GetParametricCurveByType(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; if (Curve == NULL) return; ContextID = Curve ->InterpParams->ContextID; _cmsFreeInterpParams(Curve ->InterpParams); if (Curve -> Table16) _cmsFree(ContextID, Curve ->Table16); if (Curve ->Segments) { cmsUInt32Number i; for (i=0; i < Curve ->nSegments; i++) { if (Curve ->Segments[i].SampledPoints) { _cmsFree(ContextID, Curve ->Segments[i].SampledPoints); } if (Curve ->SegInterp[i] != 0) _cmsFreeInterpParams(Curve->SegInterp[i]); } _cmsFree(ContextID, Curve ->Segments); _cmsFree(ContextID, Curve ->SegInterp); } if (Curve -> Evals) _cmsFree(ContextID, Curve -> Evals); if (Curve) _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 / (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=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(cmsInt32Number 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) { 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 < 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) { cmsFloat32Number w[MAX_NODES_IN_CURVE], y[MAX_NODES_IN_CURVE], z[MAX_NODES_IN_CURVE]; int i, nItems, Zeros, Poles; if (Tab == NULL) return FALSE; if (cmsIsToneCurveLinear(Tab)) return FALSE; // Nothing to do nItems = Tab -> nEntries; if (nItems >= MAX_NODES_IN_CURVE) { cmsSignalError(Tab ->InterpParams->ContextID, cmsERROR_RANGE, "cmsSmoothToneCurve: too many points."); return FALSE; } memset(w, 0, nItems * sizeof(cmsFloat32Number)); memset(y, 0, nItems * sizeof(cmsFloat32Number)); memset(z, 0, nItems * sizeof(cmsFloat32Number)); for (i=0; i < nItems; i++) { y[i+1] = (cmsFloat32Number) Tab -> Table16[i]; w[i+1] = 1.0; } if (!smooth2(Tab ->InterpParams->ContextID, w, y, z, (cmsFloat32Number) lambda, nItems)) return FALSE; // 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]) return FALSE; // Non-Monotonic } if (Zeros > (nItems / 3)) return FALSE; // Degenerated, mostly zeros if (Poles > (nItems / 3)) return FALSE; // Degenerated, mostly poles // Seems ok for (i=0; i < nItems; i++) { // Clamp to cmsUInt16Number Tab -> Table16[i] = _cmsQuickSaturateWord(z[i+1]); } return TRUE; } // 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 enought in most cases. cmsBool CMSEXPORT cmsIsToneCurveLinear(const cmsToneCurve* Curve) { cmsUInt32Number i; int diff; _cmsAssert(Curve != NULL); for (i=0; i < 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) { int 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 < 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 = 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++; } } // 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 } Other Java examples (source code examples)Here is a short list of links related to this Java cmsgamma.c source code file: |
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