390 lines
12 KiB
C++

/*
* This file is part of RawTherapee.
*
* Copyright (c) 2004-2010 Gabor Horvath <hgabor@rawtherapee.com>
*
* RawTherapee is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* RawTherapee 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 for more details.
*
* You should have received a copy of the GNU General Public License
* along with RawTherapee. If not, see <http://www.gnu.org/licenses/>.
*/
#include "shmap.h"
#include "gauss.h"
#include "rtengine.h"
#include "rt_math.h"
#include "rawimagesource.h"
#undef THREAD_PRIORITY_NORMAL
#include "opthelper.h"
namespace rtengine {
extern const Settings* settings;
SHMap::SHMap (int w, int h, bool multiThread) : W(w), H(h), multiThread(multiThread) {
map = new float*[H];
for (int i=0; i<H; i++)
map[i] = new float[W];
}
SHMap::~SHMap () {
for (int i=0; i<H; i++)
delete [] map[i];
delete [] map;
}
void SHMap::fillLuminance( Imagefloat * img, float **luminance, double lumi[3] ) // fill with luminance
{
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i=0; i<H; i++)
for (int j=0; j<W; j++) {
luminance[i][j] = lumi[0]*std::max(img->r(i,j),0.f) + lumi[1]*std::max(img->g(i,j),0.f) + lumi[2]*std::max(img->b(i,j),0.f);
}
}
void SHMap::update (Imagefloat* img, double radius, double lumi[3], bool hq, int skip) {
if (!hq) {
fillLuminance( img, map, lumi);
#ifdef _OPENMP
#pragma omp parallel
#endif
{
AlignedBufferMP<double>* pBuffer = new AlignedBufferMP<double> (max(W,H));
gaussHorizontal<float> (map, map, *pBuffer, W, H, radius);
gaussVertical<float> (map, map, *pBuffer, W, H, radius);
delete pBuffer;
}
}
else {
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//experimental dirpyr shmap
float thresh = (100.f*radius);//1000;
// set up range function
// calculate size of Lookup table. That's possible because from a value k for all i>=k rangefn[i] will be exp(-10)
// So we use this fact and the automatic clip of lut to reduce the size of lut and the number of calculations to fill the lut
// In past this lut had only integer precision with rangefn[i] = 0 for all i>=k
// We set the last element to a small epsilon 1e-15 instead of zero to avoid divisions by zero
const int lutSize = thresh * sqrtf(10.f) + 1;
thresh *= thresh;
LUTf rangefn(lutSize);
for (int i=0; i<lutSize-1; i++) {
rangefn[i] = xexpf(-min(10.f,(static_cast<float>(i)*i) / thresh ));//*intfactor;
}
rangefn[lutSize-1] = 1e-15f;
// We need one temporary buffer
float ** buffer = allocArray<float> (W, H);
// the final result has to be in map
// for an even number of levels that means: map => buffer, buffer => map
// for an odd number of levels that means: buffer => map, map => buffer, buffer => map
// so let's calculate the number of levels first
// There are at least two levels
int numLevels=2;
int scale=2;
while (skip*scale<16) {
scale *= 2;
numLevels++;
}
float ** dirpyrlo[2];
if(numLevels&1) { // odd number of levels, start with buffer
dirpyrlo[0] = buffer;
dirpyrlo[1] = map;
} else { // even number of levels, start with map
dirpyrlo[0] = map;
dirpyrlo[1] = buffer;
}
fillLuminance( img, dirpyrlo[0], lumi);
scale = 1;
int level=0;
int indx=0;
dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );
scale *= 2;
level ++;
indx = 1-indx;
while (skip*scale<16) {
dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );
scale *= 2;
level ++;
indx = 1-indx;
}
dirpyr_shmap(dirpyrlo[indx], dirpyrlo[1-indx], W, H, rangefn, level, scale );
freeArray<float>(buffer, H);
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*
// anti-alias filtering the result
#ifdef _OPENMP
#pragma omp for
#endif
for (int i=0; i<H; i++)
for (int j=0; j<W; j++)
if (i>0 && j>0 && i<H-1 && j<W-1)
map[i][j] = (buffer[i-1][j-1]+buffer[i-1][j]+buffer[i-1][j+1]+buffer[i][j-1]+buffer[i][j]+buffer[i][j+1]+buffer[i+1][j-1]+buffer[i+1][j]+buffer[i+1][j+1])/9;
else
map[i][j] = buffer[i][j];
*/
}
// update average, minimum, maximum
double _avg = 0.0f; // use double precision to gain precision especially at systems with few cores and big pictures (error for 36 MPixel on single core was about 8% with float)
min_f = 65535;
max_f = 0;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
float _min_f = 65535.0f;
float _max_f = 0.0f;
float _val;
#ifdef _OPENMP
#pragma omp for reduction(+:_avg) schedule(dynamic,16) nowait
#endif
for (int i=0; i<H; i++)
for (int j=0; j<W; j++) {
_val = map[i][j];
if (_val < _min_f)
_min_f = _val;
if (_val > _max_f)
_max_f = _val;
_avg += _val;
}
#ifdef _OPENMP
#pragma omp critical
#endif
{
if(_min_f < min_f )
min_f = _min_f;
if(_max_f > max_f )
max_f = _max_f;
}
}
_avg /= ((H)*(W));
avg = _avg;
}
void SHMap::forceStat (float max_, float min_, float avg_) {
max_f = max_;
min_f = min_;
avg = avg_;
}
SSEFUNCTION void SHMap::dirpyr_shmap(float ** data_fine, float ** data_coarse, int width, int height, LUTf & rangefn, int level, int scale)
{
//scale is spacing of directional averaging weights
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// calculate weights, compute directionally weighted average
int scalewin, halfwin;
if(level < 2) {
halfwin = 1;
scalewin = halfwin*scale;
#ifdef _OPENMP
#pragma omp parallel
#endif
{
#if defined( __SSE2__ ) && defined( __x86_64__ )
__m128 dirwtv, valv, normv, dftemp1v, dftemp2v;
#endif // __SSE2__
int j;
#ifdef _OPENMP
#pragma omp for
#endif
for(int i = 0; i < height; i++) {
float dirwt;
for(j = 0; j < scalewin; j++) {
float val=0.f;
float norm=0.f;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j%scale; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#if defined( __SSE2__ ) && defined( __x86_64__ )
int inbrMin = max(i-scalewin,i%scale);
for(; j < (width-scalewin)-3; j+=4) {
valv= _mm_setzero_ps();
normv= _mm_setzero_ps();
dftemp1v = LVFU(data_fine[i][j]);
for(int inbr=inbrMin; inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
dftemp2v = LVFU(data_fine[inbr][jnbr]);
dirwtv = ( rangefn[_mm_cvttps_epi32(vabsf(dftemp2v-dftemp1v))] );
valv += dirwtv*dftemp2v;
normv += dirwtv;
}
}
_mm_storeu_ps( &data_coarse[i][j], valv/normv);
}
for(; j < width-scalewin; j++) {
float val=0.f;
float norm=0.f;
for(int inbr=inbrMin; inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#else
for(; j < width-scalewin; j++) {
float val=0.f;
float norm=0.f;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#endif
for(; j < width; j++) {
float val=0.f;
float norm=0.f;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<width; jnbr+=scale) {
dirwt = ( rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
}
}
}
else {
halfwin=2;
scalewin = halfwin*scale;
int domker[5][5] = {{1,1,1,1,1},{1,2,2,2,1},{1,2,2,2,1},{1,2,2,2,1},{1,1,1,1,1}};
//generate domain kernel
#ifdef _OPENMP
#pragma omp parallel
#endif
{
#if defined( __SSE2__ ) && defined( __x86_64__ )
__m128 dirwtv, valv, normv, dftemp1v, dftemp2v;
float domkerv[5][5][4] __attribute__ ((aligned (16))) = {{{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{2,2,2,2},{2,2,2,2},{2,2,2,2},{1,1,1,1}},{{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1},{1,1,1,1}}};
#endif // __SSE2__
int j;
#ifdef _OPENMP
#pragma omp for schedule(dynamic,16)
#endif
for(int i = 0; i < height; i++) {
float dirwt;
for(j = 0; j < scalewin; j++) {
float val=0.f;
float norm=0.f;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j%scale; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#if defined( __SSE2__ ) && defined( __x86_64__ )
for(; j < width-scalewin-3; j+=4) {
valv = _mm_setzero_ps();
normv = _mm_setzero_ps();
dftemp1v = LVFU(data_fine[i][j]);
for(int inbr=max(i-scalewin,i%scale); inbr<=MIN(i+scalewin, height-1); inbr+=scale) {
int indexihlp = (inbr-i)/scale+halfwin;
for (int jnbr=j-scalewin,indexjhlp = 0; jnbr<=j+scalewin; jnbr+=scale,indexjhlp++) {
dftemp2v = LVFU(data_fine[inbr][jnbr]);
dirwtv = ( _mm_load_ps((float*)&domkerv[indexihlp][indexjhlp]) * rangefn[_mm_cvttps_epi32(vabsf(dftemp2v-dftemp1v))] );
valv += dirwtv*dftemp2v;
normv += dirwtv;
}
}
_mm_storeu_ps( &data_coarse[i][j], valv/normv);
}
for(; j < width-scalewin; j++) {
float val=0;
float norm=0;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#else
for(; j < width-scalewin; j++) {
float val=0;
float norm=0;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<=j+scalewin; jnbr+=scale) {
dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
#endif
for(; j < width; j++) {
float val=0;
float norm=0;
for(int inbr=max(i-scalewin,i%scale); inbr<=min(i+scalewin, height-1); inbr+=scale) {
for (int jnbr=j-scalewin; jnbr<width; jnbr+=scale) {
dirwt = ( domker[(inbr-i)/scale+halfwin][(jnbr-j)/scale+halfwin] * rangefn[abs(data_fine[inbr][jnbr]-data_fine[i][j])] );
val += dirwt*data_fine[inbr][jnbr];
norm += dirwt;
}
}
data_coarse[i][j] = val/norm; // low pass filter
}
}
}
}
}
}//end of SHMap