--- /dev/null
+//---------------------------------------------------------------------------------
+//
+// Little Color Management System
+// Copyright (c) 1998-2010 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)
+ Val = 0;
+ else
+ Val = pow(R, Params[0]);
+ break;
+
+ // Type 1 Reversed: X = Y ^1/gamma
+ case -1:
+ if (R < 0)
+ 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;
+}
+
+
+// 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;
+
+ _cmsAssert(t != NULL);
+
+ n = t ->nEntries;
+ last = t ->Table16[n-1];
+
+ for (i = n-2; i >= 0; --i) {
+
+ if (t ->Table16[i] > last)
+
+ 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
+}
projects / openjpeg.git / blobdiff