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merge with dev

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This commit is contained in:
Desmis
2019-04-18 08:26:47 +02:00
parent 241fb8fdb9 40fe266e21
commit d78ed42ee0
5 changed files with 113 additions and 139 deletions
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159
rtengine/FTblockDN.cc
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@@ -42,6 +42,7 @@
#ifdef _OPENMP
#include <omp.h>
#endif
#define BENCHMARK
#include "StopWatch.h"
#define TS 64 // Tile size
@@ -839,6 +840,12 @@ BENCHFUN
{static_cast<float>(wprof[2][0]), static_cast<float>(wprof[2][1]), static_cast<float>(wprof[2][2])}
};
const float wpfast[3][3] = {
{static_cast<float>(wprof[0][0]) / Color::D50x, static_cast<float>(wprof[0][1]) / Color::D50x, static_cast<float>(wprof[0][2]) / Color::D50x},
{static_cast<float>(wprof[1][0]), static_cast<float>(wprof[1][1]), static_cast<float>(wprof[1][2])},
{static_cast<float>(wprof[2][0]) / Color::D50z, static_cast<float>(wprof[2][1]) / Color::D50z, static_cast<float>(wprof[2][2]) / Color::D50z}
};
// begin tile processing of image
#ifdef _OPENMP
#pragma omp parallel num_threads(numthreads) if (numthreads>1)
@@ -925,51 +932,38 @@ BENCHFUN
if (!denoiseMethodRgb) { //lab mode
//modification Jacques feb 2013 and july 2014
#ifdef _OPENMP
#pragma omp parallel for num_threads(denoiseNestedLevels) if (denoiseNestedLevels>1)
#pragma omp parallel for schedule(dynamic,16) num_threads(denoiseNestedLevels) if (denoiseNestedLevels>1)
#endif
for (int i = tiletop; i < tilebottom; ++i) {
int i1 = i - tiletop;
const int i1 = i - tiletop;
for (int j = tileleft; j < tileright; ++j) {
int j1 = j - tileleft;
float R_ = gain * src->r(i, j);
float G_ = gain * src->g(i, j);
float B_ = gain * src->b(i, j);
const int j1 = j - tileleft;
R_ = Color::denoiseIGammaTab[R_];
G_ = Color::denoiseIGammaTab[G_];
B_ = Color::denoiseIGammaTab[B_];
const float R_ = Color::denoiseIGammaTab[gain * src->r(i, j)];
const float G_ = Color::denoiseIGammaTab[gain * src->g(i, j)];
const float B_ = Color::denoiseIGammaTab[gain * src->b(i, j)];
//apply gamma noise standard (slider)
R_ = R_ < 65535.f ? gamcurve[R_] : (Color::gammanf(R_ / 65535.f, gam) * 32768.f);
G_ = G_ < 65535.f ? gamcurve[G_] : (Color::gammanf(G_ / 65535.f, gam) * 32768.f);
B_ = B_ < 65535.f ? gamcurve[B_] : (Color::gammanf(B_ / 65535.f, gam) * 32768.f);
//true conversion xyz=>Lab
float X, Y, Z;
Color::rgbxyz(R_, G_, B_, X, Y, Z, wp);
//convert to Lab
float L, a, b;
Color::XYZ2Lab(X, Y, Z, L, a, b);
labdn->L[i1][j1] = L;
labdn->a[i1][j1] = a;
labdn->b[i1][j1] = b;
labdn->L[i1][j1] = R_ < 65535.f ? gamcurve[R_] : Color::gammanf(R_ / 65535.f, gam) * 32768.f;
labdn->a[i1][j1] = G_ < 65535.f ? gamcurve[G_] : Color::gammanf(G_ / 65535.f, gam) * 32768.f;
labdn->b[i1][j1] = B_ < 65535.f ? gamcurve[B_] : Color::gammanf(B_ / 65535.f, gam) * 32768.f;
if (((i1 | j1) & 1) == 0) {
if (numTries == 1) {
noisevarlum[(i1 >> 1)*width2 + (j1 >> 1)] = useNoiseLCurve ? lumcalc[i >> 1][j >> 1] : noisevarL;
noisevarchrom[(i1 >> 1)*width2 + (j1 >> 1)] = useNoiseCCurve ? maxNoiseVarab * ccalc[i >> 1][j >> 1] : 1.f;
noisevarlum[(i1 >> 1) * width2 + (j1 >> 1)] = useNoiseLCurve ? lumcalc[i >> 1][j >> 1] : noisevarL;
noisevarchrom[(i1 >> 1) * width2 + (j1 >> 1)] = useNoiseCCurve ? maxNoiseVarab * ccalc[i >> 1][j >> 1] : 1.f;
} else {
noisevarlum[(i1 >> 1)*width2 + (j1 >> 1)] = lumcalc[i >> 1][j >> 1];
noisevarchrom[(i1 >> 1)*width2 + (j1 >> 1)] = ccalc[i >> 1][j >> 1];
noisevarlum[(i1 >> 1) * width2 + (j1 >> 1)] = lumcalc[i >> 1][j >> 1];
noisevarchrom[(i1 >> 1) * width2 + (j1 >> 1)] = ccalc[i >> 1][j >> 1];
}
}
//end chroma
}
//true conversion xyz=>Lab
Color::RGB2Lab(labdn->L[i1], labdn->a[i1], labdn->b[i1], labdn->L[i1], labdn->a[i1], labdn->b[i1], wpfast, width);
}
} else {//RGB mode
#ifdef _OPENMP
@@ -1606,27 +1600,13 @@ BENCHFUN
for (int i = tiletop; i < tilebottom; ++i) {
int i1 = i - tiletop;
//true conversion Lab==>xyz
Color::Lab2RGBLimit(labdn->L[i1], labdn->a[i1], labdn->b[i1], labdn->L[i1], labdn->a[i1], labdn->b[i1], wip, 9000000.f, 1.f + qhighFactor * realred, 1.f + qhighFactor * realblue, width);
for (int j = tileleft; j < tileright; ++j) {
int j1 = j - tileleft;
//modification Jacques feb 2013
//true conversion Lab==>xyz
float L = labdn->L[i1][j1];
float a = labdn->a[i1][j1];
float b = labdn->b[i1][j1];
float c_h = SQR(a) + SQR(b);
if (c_h > 9000000.f) {
a *= 1.f + qhighFactor * realred;
b *= 1.f + qhighFactor * realblue;
}
//convert XYZ
float X, Y, Z;
Color::Lab2XYZ(L, a, b, X, Y, Z);
//apply inverse gamma noise
float r_, g_, b_;
Color::xyz2rgb(X, Y, Z, r_, g_, b_, wip);
float r_ = labdn->L[i1][j1];
float g_ = labdn->a[i1][j1];
float b_ = labdn->b[i1][j1];
//inverse gamma standard (slider)
r_ = r_ < 32768.f ? igamcurve[r_] : (Color::gammanf(r_ / 32768.f, igam) * 65535.f);
g_ = g_ < 32768.f ? igamcurve[g_] : (Color::gammanf(g_ / 32768.f, igam) * 65535.f);
@@ -2132,52 +2112,7 @@ void ImProcFunctions::RGBoutput_tile_row(float *bloxrow_L, float ** Ldetail, flo
#undef epsilon
*/
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
float ImProcFunctions::MadMax(float * DataList, int & max, int datalen)
{
//computes Median Absolute Deviation and Maximum of DataList
//DataList values should mostly have abs val < 65535
int * histo = new int[65536];
//memset(histo, 0, 65536*sizeof(histo));
for (int i = 0; i < 65536; ++i) {
histo[i] = 0;
}
//calculate histogram of absolute values of HH wavelet coeffs
for (int i = 0; i < datalen; ++i) {
histo[MAX(0, MIN(65535, abs((int)DataList[i])))]++;
}
//find median of histogram
int median = 0, count = 0;
while (count < datalen / 2) {
count += histo[median];
++median;
}
//find max of histogram
max = 65535;
while (histo[max] == 0) {
max--;
}
int count_ = count - histo[median - 1];
delete[] histo;
// interpolate
return (((median - 1) + (datalen / 2 - count_) / (static_cast<float>(count - count_))) / 0.6745);
}
float ImProcFunctions::Mad(float * DataList, const int datalen)
float ImProcFunctions::Mad(const float * DataList, const int datalen)
{
if (datalen <= 1) { // Avoid possible buffer underrun
return 0;
@@ -2189,7 +2124,7 @@ float ImProcFunctions::Mad(float * DataList, const int datalen)
//calculate histogram of absolute values of wavelet coeffs
for (int i = 0; i < datalen; ++i) {
histo[min(255, abs(static_cast<int>(DataList[i])))]++;
histo[static_cast<int>(rtengine::min(255.f, fabsf(DataList[i])))]++;
}
//find median of histogram
@@ -2206,7 +2141,7 @@ float ImProcFunctions::Mad(float * DataList, const int datalen)
return (((median - 1) + (datalen / 2 - count_) / (static_cast<float>(count - count_))) / 0.6745);
}
float ImProcFunctions::MadRgb(float * DataList, const int datalen)
float ImProcFunctions::MadRgb(const float * DataList, const int datalen)
{
if (datalen <= 1) { // Avoid possible buffer underrun
return 0;
@@ -2221,10 +2156,8 @@ float ImProcFunctions::MadRgb(float * DataList, const int datalen)
}
//calculate histogram of absolute values of wavelet coeffs
int i;
for (i = 0; i < datalen; ++i) {
histo[min(65535, abs(static_cast<int>(DataList[i])))]++;
for (int i = 0; i < datalen; ++i) {
histo[static_cast<int>(rtengine::min(65535.f, fabsf(DataList[i])))]++;
}
//find median of histogram
@@ -2244,27 +2177,23 @@ float ImProcFunctions::MadRgb(float * DataList, const int datalen)
void ImProcFunctions::Noise_residualAB(wavelet_decomposition &WaveletCoeffs_ab, float &chresid, float &chmaxresid, bool denoiseMethodRgb)
void ImProcFunctions::Noise_residualAB(const wavelet_decomposition &WaveletCoeffs_ab, float &chresid, float &chmaxresid, bool denoiseMethodRgb)
{
int maxlvl = WaveletCoeffs_ab.maxlevel();
float resid = 0.f;
float madC;
float maxresid = 0.f;
for (int lvl = 0; lvl < maxlvl; ++lvl) {
#ifdef _OPENMP
#pragma omp parallel for schedule(dynamic) collapse(2) reduction(+:resid) reduction(max:maxresid) num_threads(denoiseNestedLevels) if (denoiseNestedLevels>1)
#endif
for (int lvl = 0; lvl < WaveletCoeffs_ab.maxlevel(); ++lvl) {
// compute median absolute deviation (MAD) of detail coefficients as robust noise estimator
int Wlvl_ab = WaveletCoeffs_ab.level_W(lvl);
int Hlvl_ab = WaveletCoeffs_ab.level_H(lvl);
float ** WavCoeffs_ab = WaveletCoeffs_ab.level_coeffs(lvl);
for (int dir = 1; dir < 4; ++dir) {
if (denoiseMethodRgb) {
madC = SQR(MadRgb(WavCoeffs_ab[dir], Wlvl_ab * Hlvl_ab));
} else {
madC = SQR(Mad(WavCoeffs_ab[dir], Wlvl_ab * Hlvl_ab));
}
const int Wlvl_ab = WaveletCoeffs_ab.level_W(lvl);
const int Hlvl_ab = WaveletCoeffs_ab.level_H(lvl);
float ** WavCoeffs_ab = WaveletCoeffs_ab.level_coeffs(lvl);
const float madC = SQR(denoiseMethodRgb ? MadRgb(WavCoeffs_ab[dir], Wlvl_ab * Hlvl_ab) : Mad(WavCoeffs_ab[dir], Wlvl_ab * Hlvl_ab));
resid += madC;
@@ -2742,7 +2671,7 @@ bool ImProcFunctions::WaveletDenoiseAllAB(wavelet_decomposition &WaveletCoeffs_L
if (!memoryAllocationFailed) {
#ifdef _OPENMP
#pragma omp for schedule(dynamic) collapse(2)
#pragma omp for schedule(dynamic) collapse(2) nowait
#endif
for (int lvl = 0; lvl < maxlvl; ++lvl) {