Pipette and "On Preview Widgets" branch. See issue 227
The pipette part is already working quite nice but need to be finished. The widgets part needs more work...
This commit is contained in:
Hombre
704
rtengine/dirpyrLab_denoise.cc
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704
rtengine/dirpyrLab_denoise.cc
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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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* <20> 2010 Emil Martinec <ejmartin@uchicago.edu>
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*
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*/
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#include <cstddef>
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#include <cmath>
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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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#include "array2D.h"
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#include "rt_math.h"
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#define CLIPC(a) ((a)>-32000?((a)<32000?(a):32000):-32000)
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#define DIRWT_L(i1,j1,i,j) ( rangefn_L[(data_fine->L[i1][j1]-data_fine->L[i][j]+32768)] )
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#define DIRWT_AB(i1,j1,i,j) ( rangefn_ab[(data_fine->a[i1][j1]-data_fine->a[i][j]+32768)] * \
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rangefn_ab[(data_fine->L[i1][j1]-data_fine->L[i][j]+32768)] * \
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rangefn_ab[(data_fine->b[i1][j1]-data_fine->b[i][j]+32768)] )
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//#define NRWT_L(a) (nrwt_l[a] )
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#define NRWT_AB (nrwt_ab[(hipass[1]+32768)] * nrwt_ab[(hipass[2]+32768)])
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#define med3(a,b,c) (a<b ? (b<c ? b : (a<c ? c : a)) : (a<c ? a : (b<c ? c : b)))
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#define hmf(a11,a12,a13,a21,a22,a23,a31,a32,a33) \
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(med3(a22,med3(a22,med3(a12,a22,a32),med3(a21,a22,a23)), \
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med3(a22,med3(a11,a22,a33),med3(a13,a22,a31))) )
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#define PIX_SORT(a,b) { if ((a)>(b)) {temp=(a);(a)=(b);(b)=temp;} }
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#define med3x3(a0,a1,a2,a3,a4,a5,a6,a7,a8,median) { \
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p[0]=a0; p[1]=a1; p[2]=a2; p[3]=a3; p[4]=a4; p[5]=a5; p[6]=a6; p[7]=a7; p[8]=a8; \
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PIX_SORT(p[1],p[2]); PIX_SORT(p[4],p[5]); PIX_SORT(p[7],p[8]); \
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PIX_SORT(p[0],p[1]); PIX_SORT(p[3],p[4]); PIX_SORT(p[6],p[7]); \
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PIX_SORT(p[1],p[2]); PIX_SORT(p[4],p[5]); PIX_SORT(p[7],p[8]); \
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PIX_SORT(p[0],p[3]); PIX_SORT(p[5],p[8]); PIX_SORT(p[4],p[7]); \
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PIX_SORT(p[3],p[6]); PIX_SORT(p[1],p[4]); PIX_SORT(p[2],p[5]); \
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PIX_SORT(p[4],p[7]); PIX_SORT(p[4],p[2]); PIX_SORT(p[6],p[4]); \
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PIX_SORT(p[4],p[2]); median=p[4];} //a4 is the median
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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 procparams::DirPyrDenoiseParams & dnparams )
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{
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float gam = dnparams.gamma/3.0;
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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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LUTf gamcurve(65536,0);
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//DiagonalCurve* lumacurve = new DiagonalCurve (dnparams.lumcurve, CURVES_MIN_POLY_POINTS);
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//DiagonalCurve* chromacurve = new DiagonalCurve (dnparams.chromcurve, CURVES_MIN_POLY_POINTS);
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//LUTf Lcurve(65536);
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//LUTf abcurve(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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gamcurve[i] = CLIP(g);
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/*float val = (float)i/65535.0;
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float Lval = (2*(lumacurve->getVal(val)));
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float abval = (2*(chromacurve->getVal(val)));
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Lcurve[i] = SQR(Lval);
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abcurve[i] = SQR(abval);
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if (i % 1000 ==0) printf("%d Lmult=%f abmult=%f \n",i,Lcurve[i],abcurve[i]);*/
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}
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//delete lumacurve;
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//delete chromacurve;
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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] = CurveFactory::flinterp(gamcurve,src->L[i][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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LUTf rangefn_L(65536);
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LUTf nrwt_l(65536);
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LUTf rangefn_ab(65536);
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LUTf nrwt_ab(65536);
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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<65536; 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 = 10.0*dnparams.luma;
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float noisevar_L = SQR(noise_L);
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float noise_ab = 100.0*dnparams.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<65536; i++)
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rangefn_L[i] = (( exp(-(double)fabs(i-32768) * tonefactor / (1.0+noise_L)) * (1.0+noisevar_L)/((double)(i-32768)*(double)(i-32768) + noisevar_L+1.0)));
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for (int i=0; i<65536; i++)
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rangefn_ab[i] = (( exp(-(double)fabs(i-32768) * tonefactor / (1.0+3*noise_ab)) * (1.0+noisevar_ab)/((double)(i-32768)*(double)(i-32768) + noisevar_ab+1.0)));
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for (int i=0; i<65536; i++)
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nrwt_ab[i] = ((1.0+abs(i-32768)/(1.0+8*noise_ab)) * exp(-(double)fabs(i-32768)/ (1.0+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, dnparams.luma, dnparams.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, dnparams.luma, dnparams.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, rangefn_L, nrwt_l, nrwt_ab, pitch, scale, dnparams.luma, dnparams.chroma/*, Lcurve, abcurve*/ );
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}
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scale = scales[0];
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pitch = pitches[0];
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// freeing as much memory as possible since the next call to idirpyr will need lots
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for(int i = 1; i < maxlevel; i++) {
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delete dirpyrLablo[i];
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}
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idirpyr(dirpyrLablo[0], dst, 0, rangefn_L, nrwt_l, nrwt_ab, pitch, scale, dnparams.luma, dnparams.chroma/*, Lcurve, abcurve*/ );
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// freeing the last bunch of memory
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delete dirpyrLablo[0];
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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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gamcurve[i] = (CurveFactory::gamma((float)i/65535.0, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0);
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}
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if (dnparams.luma>0) {
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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[dst->L[i][j]];
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}
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} else {
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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[src->L[i][j]];
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}
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}
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}
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void ImProcFunctions::dirpyr(LabImage* data_fine, LabImage* data_coarse, int level,
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LUTf & rangefn_L, LUTf & rangefn_ab, int pitch, int scale,
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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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#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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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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for(int inbr=(i-scalewin); inbr<=(i+scalewin); inbr+=scale) {
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if (inbr<0 || inbr>height-1) continue;
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for (int jnbr=(j-scalewin); jnbr<=(j+scalewin); jnbr+=scale) {
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if (jnbr<0 || jnbr>width-1) continue;
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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]=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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/*if (level<2 && i>0 && i<height-1 && j>0 && j<width-1) {
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Lhmf = hmf(data_fine->L[i-1][j-1], data_fine->L[i-1][j], data_fine->L[i-1][j+1], \
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data_fine->L[i][j-1], data_fine->L[i][j], data_fine->L[i][j+1], \
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data_fine->L[i+1][j-1], data_fine->L[i+1][j], data_fine->L[i+1][j+1]);
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//med3x3(data_fine->L[i-1][j-1], data_fine->L[i-1][j], data_fine->L[i-1][j+1], \
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data_fine->L[i][j-1], data_fine->L[i][j], data_fine->L[i][j+1], \
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data_fine->L[i+1][j-1], data_fine->L[i+1][j], data_fine->L[i+1][j+1],Lmed);
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data_coarse->L[i1][j1] = Lhmf;
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}*/
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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, LUTf &rangefn_L, LUTf & nrwt_l, LUTf & nrwt_ab,
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int pitch, int scale, const int luma, const int chroma/*, LUTf & Lcurve, LUTf & abcurve*/ )
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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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array2D<float> nrfactorL (width,height);
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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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noisevar_L *= scalefactor;
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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
|
||||
// (2) subtract smoothed image at level n-1 from lopass image at level n-1 to make hipass image at level n-1
|
||||
// (3) denoise the hipass image at level n-1
|
||||
// (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
|
||||
|
||||
// note that the coarsest level amounts to skipping step (1) and doing (2,3,4).
|
||||
// in other words, skip step one if pitch=1
|
||||
|
||||
// step (1)
|
||||
|
||||
if (pitch==1) {
|
||||
|
||||
// step (1-2-3-4)
|
||||
|
||||
#ifdef _OPENMP
|
||||
#pragma omp parallel
|
||||
#endif
|
||||
{
|
||||
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
for(int i = 0; i < height; i++)
|
||||
for(int j = 0; j < width; j++) {
|
||||
float hipass[3], hpffluct[3], tonefactor, nrfactor;
|
||||
|
||||
tonefactor = (nrwt_l[data_coarse->L[i][j]]);
|
||||
|
||||
hipass[1] = data_fine->a[i][j]-data_coarse->a[i][j];
|
||||
hipass[2] = data_fine->b[i][j]-data_coarse->b[i][j];
|
||||
|
||||
//Wiener filter
|
||||
//luma
|
||||
if (level<2) {
|
||||
hipass[0] = data_fine->L[i][j]-data_coarse->L[i][j];
|
||||
hpffluct[0]=SQR(hipass[0])+SQR(hipass[1])+SQR(hipass[2])+0.001;
|
||||
nrfactorL[i][j] = (1.0+hpffluct[0])/(1.0+hpffluct[0]+noisevar_L /* * Lcurve[data_coarse->L[i][j]]*/);
|
||||
//hipass[0] *= hpffluct[0]/(hpffluct[0]+noisevar_L);
|
||||
//data_fine->L[i][j] = CLIP(hipass[0]+data_coarse->L[i][j]);
|
||||
}
|
||||
|
||||
//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];
|
||||
}
|
||||
|
||||
if (level<2) {
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
for(int i = 0; i < height; i++)
|
||||
for(int j = 0; j < width; j++) {
|
||||
|
||||
float dirwt_l, norm_l;
|
||||
float nrfctrave=0;
|
||||
norm_l = 0;//if we do want to include the input pixel in the sum
|
||||
|
||||
for(int inbr=max(0,i-1); inbr<=min(height-1,i+1); inbr++) {
|
||||
for (int jnbr=max(0,j-1); jnbr<=min(width-1,j+1); jnbr++) {
|
||||
dirwt_l = DIRWT_L(inbr, jnbr, i, j);
|
||||
nrfctrave += dirwt_l*nrfactorL[inbr][jnbr];
|
||||
norm_l += dirwt_l;
|
||||
}
|
||||
}
|
||||
|
||||
nrfctrave /= norm_l;
|
||||
//nrfctrave = nrfactorL[i][j];
|
||||
//nrfctrave=1;
|
||||
|
||||
float hipass[3];
|
||||
|
||||
//luma
|
||||
|
||||
/*if (i>0 && i<height-1 && j>0 && j<width-1) {
|
||||
med3x3(nrfactorL[i-1][j-1], nrfactorL[i-1][j], nrfactorL[i-1][j+1], \
|
||||
nrfactorL[i][j-1], nrfactorL[i][j], nrfactorL[i][j+1], \
|
||||
nrfactorL[i+1][j-1], nrfactorL[i+1][j], nrfactorL[i+1][j+1], median);
|
||||
//median = hmf(nrfactorL[i-1][j-1], nrfactorL[i-1][j], nrfactorL[i-1][j+1], \
|
||||
nrfactorL[i][j-1], nrfactorL[i][j], nrfactorL[i][j+1], \
|
||||
nrfactorL[i+1][j-1], nrfactorL[i+1][j], nrfactorL[i+1][j+1]);
|
||||
//median = nrfactorL[i][j];
|
||||
} else {
|
||||
median = nrfactorL[i][j];
|
||||
}*/
|
||||
hipass[0] = nrfctrave*(data_fine->L[i][j]-data_coarse->L[i][j]);
|
||||
//hipass[0] = median*(data_fine->L[i][j]-data_coarse->L[i][j]);
|
||||
//hipass[0] = nrfactorL[i][j]*(data_fine->L[i][j]-data_coarse->L[i][j]);
|
||||
data_fine->L[i][j] = CLIP(hipass[0]+data_coarse->L[i][j]);
|
||||
|
||||
//chroma
|
||||
//hipass[1] = nrfactorab[i][j]*(data_fine->a[i][j]-data_coarse->a[i][j]);
|
||||
//hipass[2] = nrfactorab[i][j]*(data_fine->b[i][j]-data_coarse->b[i][j]);
|
||||
|
||||
//data_fine->a[i][j] = hipass[1]+data_coarse->a[i][j];
|
||||
//data_fine->b[i][j] = hipass[2]+data_coarse->b[i][j];
|
||||
}
|
||||
}//end of luminance correction
|
||||
|
||||
|
||||
|
||||
}//end of pitch=1
|
||||
|
||||
} else {//pitch>1
|
||||
|
||||
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++) {
|
||||
|
||||
float tonefactor = (nrwt_l[smooth->L[i][j]]);
|
||||
//double wtdsum[3], norm;
|
||||
float hipass[3], hpffluct[3], nrfactor;
|
||||
|
||||
hipass[1] = data_fine->a[i][j]-smooth->a[i][j];
|
||||
hipass[2] = data_fine->b[i][j]-smooth->b[i][j];
|
||||
|
||||
//Wiener filter
|
||||
//luma
|
||||
if (level<2) {
|
||||
hipass[0] = data_fine->L[i][j]-smooth->L[i][j];
|
||||
hpffluct[0]=SQR(hipass[0])+SQR(hipass[1])+SQR(hipass[2])+0.001;
|
||||
nrfactorL[i][j] = (1.0+hpffluct[0])/(1.0+hpffluct[0]+noisevar_L /* * Lcurve[smooth->L[i][j]]*/);
|
||||
//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 /* * abcurve[smooth->L[i][j]]*/);
|
||||
|
||||
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];
|
||||
}
|
||||
|
||||
|
||||
if (level<2) {
|
||||
#ifdef _OPENMP
|
||||
#pragma omp for
|
||||
#endif
|
||||
for(int i = 0; i < height; i++)
|
||||
for(int j = 0; j < width; j++) {
|
||||
|
||||
float dirwt_l, norm_l;
|
||||
float nrfctrave=0;
|
||||
norm_l = 0;//if we do want to include the input pixel in the sum
|
||||
|
||||
for(int inbr=(i-pitch); inbr<=(i+pitch); inbr+=pitch) {
|
||||
if (inbr<0 || inbr>height-1) continue;
|
||||
for (int jnbr=(j-pitch); jnbr<=(j+pitch); jnbr+=pitch) {
|
||||
if (jnbr<0 || jnbr>width-1) continue;
|
||||
dirwt_l = DIRWT_L(inbr, jnbr, i, j);
|
||||
nrfctrave += dirwt_l*nrfactorL[inbr][jnbr];
|
||||
norm_l += dirwt_l;
|
||||
}
|
||||
}
|
||||
|
||||
nrfctrave /= norm_l;
|
||||
//nrfctrave = nrfactorL[i][j];
|
||||
//nrfctrave=1;
|
||||
|
||||
|
||||
float hipass[3];
|
||||
|
||||
//luma
|
||||
|
||||
/*if (i>0 && i<height-1 && j>0 && j<width-1) {
|
||||
//med3x3(nrfactorL[i-1][j-1], nrfactorL[i-1][j], nrfactorL[i-1][j+1], \
|
||||
nrfactorL[i][j-1], nrfactorL[i][j], nrfactorL[i][j+1], \
|
||||
nrfactorL[i+1][j-1], nrfactorL[i+1][j], nrfactorL[i+1][j+1], median);
|
||||
median = hmf(nrfactorL[i-1][j-1], nrfactorL[i-1][j], nrfactorL[i-1][j+1], \
|
||||
nrfactorL[i][j-1], nrfactorL[i][j], nrfactorL[i][j+1], \
|
||||
nrfactorL[i+1][j-1], nrfactorL[i+1][j], nrfactorL[i+1][j+1]);
|
||||
} else {
|
||||
median = nrfactorL[i][j];
|
||||
}*/
|
||||
hipass[0] = nrfctrave*(data_fine->L[i][j]-smooth->L[i][j]);
|
||||
//hipass[0] = median*(data_fine->L[i][j]-smooth->L[i][j]);
|
||||
//hipass[0] = nrfactorL[i][j]*(data_fine->L[i][j]-data_coarse->L[i][j]);
|
||||
data_fine->L[i][j] = CLIP(hipass[0]+smooth->L[i][j]);
|
||||
|
||||
|
||||
//chroma
|
||||
//hipass[1] = nrfactorab[i][j]*(data_fine->a[i][j]-data_coarse->a[i][j]);
|
||||
//hipass[2] = nrfactorab[i][j]*(data_fine->b[i][j]-data_coarse->b[i][j]);
|
||||
|
||||
//data_fine->a[i][j] = hipass[1]+data_coarse->a[i][j];
|
||||
//data_fine->b[i][j] = hipass[2]+data_coarse->b[i][j];
|
||||
}
|
||||
}//end of luminance correction
|
||||
|
||||
|
||||
} // 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