Changes to black compression and saturation controls. Black compression from 0-50 acts the same as 0-100 on the previous version, compressing dark tones without crushing blacks. 50-100 then starts crushing blacks until by 100 on the slider, all tones up to the set black point are sent to zero. In the new saturation control, negative values of the slider set a linear curve rather than an inverted S curve, and smoothly decrease saturation to zero across the board.
This commit is contained in:
Emil Martinec
567
rtengine/dirpyrLab_denoise.cc
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567
rtengine/dirpyrLab_denoise.cc
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@@ -0,0 +1,567 @@
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/*
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* This file is part of RawTherapee.
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*
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* RawTherapee is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* RawTherapee is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with RawTherapee. If not, see <http://www.gnu.org/licenses/>.
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*
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* © 2010 Emil Martinec <ejmartin@uchicago.edu>
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*
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*/
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//#include <rtengine.h>
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#include <cstddef>
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#include <math.h>
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#include <curves.h>
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#include <labimage.h>
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#include <improcfun.h>
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#define SQR(x) ((x)*(x))
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#define CLIPTO(a,b,c) ((a)>(b)?((a)<(c)?(a):(c)):(b))
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#define CLIPC(a) ((a)>-32000?((a)<32000?(a):32000):-32000)
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#define CLIP(a) (CLIPTO(a,0,65535))
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#define DIRWT_L(i1,j1,i,j) (/*domker[(i1-i)/scale+halfwin][(j1-j)/scale+halfwin] */ rangefn_L[(int)(data_fine->L[i1][j1]-data_fine->L[i][j]+0x10000)] )
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#define DIRWT_AB(i1,j1,i,j) ( /*domker[(i1-i)/scale+halfwin][(j1-j)/scale+halfwin]*/ rangefn_ab[(int)(data_fine->a[i1][j1]-data_fine->a[i][j]+0x10000)] * \
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rangefn_ab[(int)(data_fine->L[i1][j1]-data_fine->L[i][j]+0x10000)] * \
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rangefn_ab[(int)(data_fine->b[i1][j1]-data_fine->b[i][j]+0x10000)] )
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#define NRWT_L(a) (nrwt_l[a] )
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#define NRWT_AB (nrwt_ab[(int)((hipass[1]+0x10000))] * nrwt_ab[(int)((hipass[2]+0x10000))])
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namespace rtengine {
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static const int maxlevel = 4;
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//sequence of scales
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//static const int scales[8] = {1,2,4,8,16,32,64,128};
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//sequence of pitches
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//static const int pitches[8] = {1,1,1,1,1,1,1,1};
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//sequence of scales
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//static const int scales[8] = {1,1,1,1,1,1,1,1};
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//sequence of pitches
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//static const int pitches[8] = {2,2,2,2,2,2,2,2};
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//sequence of scales
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//static const int scales[8] = {1,1,2,2,4,4,8,8};
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//sequence of pitches
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//static const int pitches[8] = {2,1,2,1,2,1,2,1};
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//sequence of scales
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static const int scales[8] = {1,1,2,4,8,16,32,64};
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//sequence of pitches
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static const int pitches[8] = {2,1,1,1,1,1,1,1};
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//pitch is spacing of subsampling
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//scale is spacing of directional averaging weights
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//example 1: no subsampling at any level -- pitch=1, scale=2^n
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//example 2: subsampling by 2 every level -- pitch=2, scale=1 at each level
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//example 3: no subsampling at first level, subsampling by 2 thereafter --
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// pitch =1, scale=1 at first level; pitch=2, scale=2 thereafter
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void ImProcFunctions :: dirpyrLab_denoise(LabImage * src, LabImage * dst, const int luma, const int chroma, float gam )
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{
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//float gam = 2.0;//MIN(3.0, 0.1*fabs(c[4])/3.0+0.001);
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float gamthresh = 0.03;
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float gamslope = exp(log((double)gamthresh)/gam)/gamthresh;
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unsigned short gamcurve[65536];
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for (int i=0; i<65536; i++) {
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int g = (int)(CurveFactory::gamma((double)i/65535.0, gam, gamthresh, gamslope, 1.0, 0.0) * 65535.0);
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//if (i<500) printf("%d %d \n",i,g);
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gamcurve[i] = CLIP(g);
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}
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//#pragma omp parallel for if (multiThread)
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for (int i=0; i<src->H; i++) {
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for (int j=0; j<src->W; j++) {
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src->L[i][j] = gamcurve[src->L[i][j] ];
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}
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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int * rangefn_L = new int [0x20000];
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float * nrwt_l = new float [0x10000];
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int * rangefn_ab = new int [0x20000];
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float * nrwt_ab = new float [0x20000];
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int intfactor = 1024;//16384;
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//set up NR weight functions
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//gamma correction for chroma in shadows
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float nrwtl_norm = ((CurveFactory::gamma((double)65535.0/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)) - \
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(CurveFactory::gamma((double)75535.0/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)));
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for (int i=0; i<0x10000; i++) {
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nrwt_l[i] = ((CurveFactory::gamma((double)i/65535.0, gam, gamthresh, gamslope, 1.0, 0.0) - \
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CurveFactory::gamma((double)(i+10000)/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)) )/nrwtl_norm;
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//if (i % 100 ==0) printf("%d %f \n",i,nrwt_l[i]);
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}
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float tonefactor = nrwt_l[32768];
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float noise_L = 25.0*luma;
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float noisevar_L = 4*SQR(noise_L);
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float noise_ab = 25*chroma;
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float noisevar_ab = SQR(noise_ab);
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//set up range functions
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for (int i=0; i<0x20000; i++)
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rangefn_L[i] = (int)(( exp(-(double)fabs(i-0x10000) * tonefactor / (1+3*noise_L)) * noisevar_L/((double)(i-0x10000)*(double)(i-0x10000) + noisevar_L))*intfactor);
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for (int i=0; i<0x20000; i++)
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rangefn_ab[i] = (int)(( exp(-(double)fabs(i-0x10000) * tonefactor / (1+3*noise_ab)) * noisevar_ab/((double)(i-0x10000)*(double)(i-0x10000) + noisevar_ab))*intfactor);
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for (int i=0; i<0x20000; i++)
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nrwt_ab[i] = ((1+abs(i-0x10000)/(1+8*noise_ab)) * exp(-(double)fabs(i-0x10000)/ (1+8*noise_ab) ) );
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//for (int i=0; i<65536; i+=100) printf("%d %d \n",i,gamcurve[i]);
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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int level;
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LabImage * dirpyrLablo[maxlevel];
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int w = (int)((src->W-1)/pitches[0])+1;
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int h = (int)((src->H-1)/pitches[0])+1;
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dirpyrLablo[0] = new LabImage(w, h);
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for (level=1; level<maxlevel; level++) {
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w = (int)((w-1)/pitches[level])+1;
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h = (int)((h-1)/pitches[level])+1;
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dirpyrLablo[level] = new LabImage(w, h);
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};
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//////////////////////////////////////////////////////////////////////////////
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// c[0] = luma = noise_L
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// c[1] = chroma = noise_ab
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// c[2] decrease of noise var with scale
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// c[3] radius of domain blur at each level
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// c[4] shadow smoothing
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// c[5] edge preservation
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level = 0;
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int scale = scales[level];
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int pitch = pitches[level];
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//int thresh = 10 * c[8];
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//impulse_nr (src, src, m_w1, m_h1, thresh, noisevar);
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dirpyr(src, dirpyrLablo[0], 0, rangefn_L, rangefn_ab, pitch, scale, luma, chroma );
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level = 1;
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while(level < maxlevel)
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{
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scale = scales[level];
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pitch = pitches[level];
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dirpyr(dirpyrLablo[level-1], dirpyrLablo[level], level, rangefn_L, rangefn_ab, pitch, scale, luma, chroma );
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level ++;
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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for(int level = maxlevel - 1; level > 0; level--)
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{
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int scale = scales[level];
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int pitch = pitches[level];
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idirpyr(dirpyrLablo[level], dirpyrLablo[level-1], level, nrwt_l, nrwt_ab, pitch, scale, luma, chroma );
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}
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scale = scales[0];
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pitch = pitches[0];
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idirpyr(dirpyrLablo[0], dst, 0, nrwt_l, nrwt_ab, pitch, scale, luma, chroma );
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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float igam = 1/gam;
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float igamthresh = gamthresh*gamslope;
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float igamslope = 1/gamslope;
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for (int i=0; i<65536; i++) {
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int g = (int)(CurveFactory::gamma((float)i/65535.0, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0);
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gamcurve[i] = CLIP(g);
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}
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for (int i=0; i<dst->H; i++)
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for (int j=0; j<dst->W; j++) {
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dst->L[i][j] = gamcurve[CLIP(dst->L[i][j]) ];
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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for(int i = 0; i < maxlevel; i++)
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{
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delete dirpyrLablo[i];
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}
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delete [] rangefn_L;
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delete [] rangefn_ab;
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delete [] nrwt_l;
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delete [] nrwt_ab;
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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};
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void ImProcFunctions::dirpyr(LabImage* data_fine, LabImage* data_coarse, int level, int * rangefn_L, int * rangefn_ab, int pitch, int scale, const int luma, const int chroma )
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{
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//pitch is spacing of subsampling
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//scale is spacing of directional averaging weights
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//example 1: no subsampling at any level -- pitch=1, scale=2^n
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//example 2: subsampling by 2 every level -- pitch=2, scale=1 at each level
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//example 3: no subsampling at first level, subsampling by 2 thereafter --
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// pitch =1, scale=1 at first level; pitch=2, scale=2 thereafter
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// calculate weights, compute directionally weighted average
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int width = data_fine->W;
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int height = data_fine->H;
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//generate domain kernel
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int halfwin = 3;//MIN(ceil(2*sig),3);
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int scalewin = halfwin*scale;
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//int intfactor = 16384;
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/*float domker[7][7];
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for (int i=-halfwin; i<=halfwin; i++)
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for (int j=-halfwin; j<=halfwin; j++) {
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domker[i+halfwin][j+halfwin] = (int)(exp(-(i*i+j*j)/(2*sig*sig))*intfactor); //or should we use a value that depends on sigma???
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}*/
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//float domker[5][5] = {{1,1,1,1,1},{1,2,2,2,1},{1,2,4,2,1},{1,2,2,2,1},{1,1,1,1,1}};
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#ifdef _OPENMP
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#pragma omp parallel for
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#endif
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for(int i = 0; i < height; i+=pitch ) { int i1=i/pitch;
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for(int j = 0, j1=0; j < width; j+=pitch, j1++)
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{
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//norm = DIRWT(i, j, i, j);
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//Lout = -norm*data_fine->L[i][j];//if we don't want to include the input pixel in the sum
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//aout = -norm*data_fine->a[i][j];
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//bout = -norm*data_fine->b[i][j];
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//or
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float dirwt_l, dirwt_ab, norm_l, norm_ab;
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//float lops,aops,bops;
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float Lout, aout, bout;
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norm_l = norm_ab = 0;//if we do want to include the input pixel in the sum
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Lout = 0;
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aout = 0;
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bout = 0;
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//normab = 0;
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for(int inbr=MAX(0,i-scalewin); inbr<=MIN(height-1,i+scalewin); inbr+=scale) {
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for (int jnbr=MAX(0,j-scalewin); jnbr<=MIN(width-1,j+scalewin); jnbr+=scale) {
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dirwt_l = DIRWT_L(inbr, jnbr, i, j);
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dirwt_ab = DIRWT_AB(inbr, jnbr, i, j);
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Lout += dirwt_l*data_fine->L[inbr][jnbr];
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aout += dirwt_ab*data_fine->a[inbr][jnbr];
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bout += dirwt_ab*data_fine->b[inbr][jnbr];
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norm_l += dirwt_l;
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norm_ab += dirwt_ab;
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}
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}
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//lops = Lout/norm;//diagnostic
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//aops = aout/normab;//diagnostic
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//bops = bout/normab;//diagnostic
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//data_coarse->L[i1][j1]=0.5*(data_fine->L[i][j]+Lout/norm_l);//low pass filter
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//data_coarse->a[i1][j1]=0.5*(data_fine->a[i][j]+aout/norm_ab);
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//data_coarse->b[i1][j1]=0.5*(data_fine->b[i][j]+bout/norm_ab);
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//or
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data_coarse->L[i1][j1]=Lout/norm_l;//low pass filter
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data_coarse->a[i1][j1]=aout/norm_ab;
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data_coarse->b[i1][j1]=bout/norm_ab;
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}
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}
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};
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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void ImProcFunctions::idirpyr(LabImage* data_coarse, LabImage* data_fine, int level, float * nrwt_l, float * nrwt_ab, int pitch, int scale, const int luma, const int chroma )
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{
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int width = data_fine->W;
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int height = data_fine->H;
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//float eps = 0.0;
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// c[0] noise_L
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// c[1] noise_ab (relative to noise_L)
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// c[2] decrease of noise var with scale
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// c[3] radius of domain blur at each level
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// c[4] shadow smoothing
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float noisevar_L = 4*SQR(25.0 * luma);
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float noisevar_ab = 2*SQR(100.0 * chroma);
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float scalefactor = 1.0/pow(2.0,(level+1)*2);//change the last 2 to 1 for longer tail of higher scale NR
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//float recontrast = (1+((float)(c[6])/100.0));
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//float resaturate = 10*(1+((float)(c[7])/100.0));
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noisevar_L *= scalefactor;
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//int halfwin = 3;//MIN(ceil(2*sig),3);
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//int intfactor= 16384;
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//int winwidth=1+2*halfwin;//this belongs in calling function
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/*float domker[7][7];
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for (int i=-halfwin; i<=halfwin; i++)
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for (int j=-halfwin; j<=halfwin; j++) {
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domker[i][j] = (int)(exp(-(i*i+j*j)/(2*sig*sig))*intfactor); //or should we use a value that depends on sigma???
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}*/
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//float domker[5][5] = {{1,1,1,1,1},{1,2,2,2,1},{1,2,4,2,1},{1,2,2,2,1},{1,1,1,1,1}};
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// for coarsest level, take non-subsampled lopass image and subtract from lopass_fine to generate hipass image
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// denoise hipass image, add back into lopass_fine to generate denoised image at fine scale
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// now iterate:
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// (1) take denoised image at level n, expand and smooth using gradient weights from lopass image at level n-1
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// the result is the smoothed image at level n-1
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// (2) subtract smoothed image at level n-1 from lopass image at level n-1 to make hipass image at level n-1
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// (3) denoise the hipass image at level n-1
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// (4) add the denoised image at level n-1 to the smoothed image at level n-1 to make the denoised image at level n-1
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// note that the coarsest level amounts to skipping step (1) and doing (2,3,4).
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// in other words, skip step one if pitch=1
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// step (1)
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if (pitch==1) {
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// step (1-2-3-4)
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#ifdef _OPENMP
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#pragma omp parallel for
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#endif
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for(int i = 0; i < height; i++)
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for(int j = 0; j < width; j++) {
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double wtdsum[3], norm;
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float hipass[3], hpffluct[3], tonefactor, nrfactor;
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tonefactor = ((NRWT_L(data_coarse->L[i][j])));
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//Wiener filter
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//luma
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if (level<2) {
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hipass[0] = data_fine->L[i][j]-data_coarse->L[i][j];
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hpffluct[0]=SQR(hipass[0])+0.001;
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hipass[0] *= hpffluct[0]/(hpffluct[0]+noisevar_L);
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data_fine->L[i][j] = CLIP(hipass[0]+data_coarse->L[i][j]);
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}
|
||||
|
||||
//chroma
|
||||
hipass[1] = data_fine->a[i][j]-data_coarse->a[i][j];
|
||||
hipass[2] = data_fine->b[i][j]-data_coarse->b[i][j];
|
||||
hpffluct[1]=SQR(hipass[1]*tonefactor)+0.001;
|
||||
hpffluct[2]=SQR(hipass[2]*tonefactor)+0.001;
|
||||
nrfactor = (hpffluct[1]+hpffluct[2]) /((hpffluct[1]+hpffluct[2]) + noisevar_ab * NRWT_AB);
|
||||
|
||||
hipass[1] *= nrfactor;
|
||||
hipass[2] *= nrfactor;
|
||||
|
||||
data_fine->a[i][j] = hipass[1]+data_coarse->a[i][j];
|
||||
data_fine->b[i][j] = hipass[2]+data_coarse->b[i][j];
|
||||
}
|
||||
|
||||
} else {
|
||||
|
||||
LabImage* smooth;
|
||||
|
||||
smooth = new LabImage(width, height);
|
||||
#ifdef _OPENMP
|
||||
#pragma omp parallel
|
||||
#endif
|
||||
|
||||
{
|
||||
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
for(int i = 0; i < height; i+=pitch)
|
||||
{
|
||||
int ix=i/pitch;
|
||||
for(int j = 0, jx=0; j < width; j+=pitch, jx++) {
|
||||
|
||||
//copy common pixels
|
||||
smooth->L[i][j] = data_coarse->L[ix][jx];
|
||||
smooth->a[i][j] = data_coarse->a[ix][jx];
|
||||
smooth->b[i][j] = data_coarse->b[ix][jx];
|
||||
}
|
||||
}
|
||||
//if (pitch>1) {//pitch=2; step (1) expand coarse image, fill in missing data
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
for(int i = 0; i < height-1; i+=2)
|
||||
for(int j = 0; j < width-1; j+=2) {
|
||||
//do midpoint first
|
||||
double norm=0.0,wtdsum[3]={0.0,0.0,0.0};
|
||||
//wtdsum[0]=wtdsum[1]=wtdsum[2]=0.0;
|
||||
for(int ix=i; ix<MIN(height,i+3); ix+=2)
|
||||
for (int jx=j; jx<MIN(width,j+3); jx+=2) {
|
||||
wtdsum[0] += smooth->L[ix][jx];
|
||||
wtdsum[1] += smooth->a[ix][jx];
|
||||
wtdsum[2] += smooth->b[ix][jx];
|
||||
norm++;
|
||||
}
|
||||
norm = 1/norm;
|
||||
smooth->L[i+1][j+1]=wtdsum[0]*norm;
|
||||
smooth->a[i+1][j+1]=wtdsum[1]*norm;
|
||||
smooth->b[i+1][j+1]=wtdsum[2]*norm;
|
||||
}
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
|
||||
for(int i = 0; i < height-1; i+=2)
|
||||
for(int j = 0; j < width-1; j+=2) {
|
||||
//now right neighbor
|
||||
if (j+1==width) continue;
|
||||
double norm=0.0,wtdsum[3]={0.0,0.0,0.0};
|
||||
|
||||
for (int jx=j; jx<MIN(width,j+3); jx+=2) {
|
||||
wtdsum[0] += smooth->L[i][jx];
|
||||
wtdsum[1] += smooth->a[i][jx];
|
||||
wtdsum[2] += smooth->b[i][jx];
|
||||
norm++;
|
||||
}
|
||||
for (int ix=MAX(0,i-1); ix<MIN(height,i+2); ix+=2) {
|
||||
wtdsum[0] += smooth->L[ix][j+1];
|
||||
wtdsum[1] += smooth->a[ix][j+1];
|
||||
wtdsum[2] += smooth->b[ix][j+1];
|
||||
norm++;
|
||||
}
|
||||
norm = 1/norm;
|
||||
smooth->L[i][j+1]=wtdsum[0]*norm;
|
||||
smooth->a[i][j+1]=wtdsum[1]*norm;
|
||||
smooth->b[i][j+1]=wtdsum[2]*norm;
|
||||
|
||||
//now down neighbor
|
||||
if (i+1==height) continue;
|
||||
norm=0.0;wtdsum[0]=wtdsum[1]=wtdsum[2]=0.0;
|
||||
for (int ix=i; ix<MIN(height,i+3); ix+=2) {
|
||||
wtdsum[0] += smooth->L[ix][j];
|
||||
wtdsum[1] += smooth->a[ix][j];
|
||||
wtdsum[2] += smooth->b[ix][j];
|
||||
norm++;
|
||||
}
|
||||
for (int jx=MAX(0,j-1); jx<MIN(width,j+2); jx+=2) {
|
||||
wtdsum[0] += smooth->L[i+1][jx];
|
||||
wtdsum[1] += smooth->a[i+1][jx];
|
||||
wtdsum[2] += smooth->b[i+1][jx];
|
||||
norm++;
|
||||
}
|
||||
norm=1/norm;
|
||||
smooth->L[i+1][j]=wtdsum[0]*norm;
|
||||
smooth->a[i+1][j]=wtdsum[1]*norm;
|
||||
smooth->b[i+1][j]=wtdsum[2]*norm;
|
||||
|
||||
}
|
||||
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
|
||||
// step (2-3-4)
|
||||
for( int i = 0; i < height; i++)
|
||||
for(int j = 0; j < width; j++) {
|
||||
|
||||
double tonefactor = ((NRWT_L(smooth->L[i][j])));
|
||||
//double wtdsum[3], norm;
|
||||
float hipass[3], hpffluct[3], nrfactor;
|
||||
//Wiener filter
|
||||
//luma
|
||||
if (level<2) {
|
||||
hipass[0] = data_fine->L[i][j]-smooth->L[i][j];
|
||||
hpffluct[0]=SQR(hipass[0])+0.001;
|
||||
hipass[0] *= hpffluct[0]/(hpffluct[0]+noisevar_L);
|
||||
data_fine->L[i][j] = CLIP(hipass[0]+smooth->L[i][j]);
|
||||
}
|
||||
|
||||
//chroma
|
||||
hipass[1] = data_fine->a[i][j]-smooth->a[i][j];
|
||||
hipass[2] = data_fine->b[i][j]-smooth->b[i][j];
|
||||
hpffluct[1]=SQR(hipass[1]*tonefactor)+0.001;
|
||||
hpffluct[2]=SQR(hipass[2]*tonefactor)+0.001;
|
||||
nrfactor = (hpffluct[1]+hpffluct[2]) /((hpffluct[1]+hpffluct[2]) + noisevar_ab * NRWT_AB);
|
||||
|
||||
hipass[1] *= nrfactor;
|
||||
hipass[2] *= nrfactor;
|
||||
|
||||
data_fine->a[i][j] = hipass[1]+smooth->a[i][j];
|
||||
data_fine->b[i][j] = hipass[2]+smooth->b[i][j];
|
||||
}
|
||||
} // end parallel
|
||||
delete smooth;
|
||||
}//end of pitch>1
|
||||
|
||||
};
|
||||
|
||||
|
||||
#undef DIRWT_L
|
||||
#undef DIRWT_AB
|
||||
|
||||
#undef NRWT_L
|
||||
#undef NRWT_AB
|
||||
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user