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*/
// 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) 1998-2022 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 typedefstruct _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 _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, conststruct _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) {
// The allocator have to follow the chain void _cmsAllocCurvesPluginChunk(struct _cmsContext_struct* ctx, conststruct _cmsContext_struct* src)
{
_cmsAssert(ctx != NULL);
// Search in type list, return position or -1 if not found static int IsInSet(int Type, _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
_cmsParametricCurvesCollection *GetParametricCurveByType(cmsContext ContextID, int Type, int* index)
{
_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)) {
_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);
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;
}
// 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)
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;
// 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) {
// 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);
}
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];
// 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;
// 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;
_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;
}
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[], conststruct _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
// 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 (!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 (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;
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);
// 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 (t->nSegments != 1) return NULL; return t->Segments[0].Params;
}
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