Tile processing implemented. Somehow in recent commits, NR settings are not being saved consistently in the pp3.
This commit is contained in:
parent
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@ -12,14 +12,13 @@ set (RTENGINESOURCEFILES safegtk.cc colortemp.cc curves.cc flatcurves.cc diagona
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processingjob.cc rtthumbnail.cc utils.cc labimage.cc slicer.cc
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iplab2rgb.cc ipsharpen.cc iptransform.cc ipresize.cc ipvibrance.cc
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jpeg_memsrc.cc jdatasrc.cc
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EdgePreserveLab.cc EdgePreservingDecomposition.cc cplx_wavelet_dec.cc FTblockDNchroma.cc
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EdgePreserveLab.cc EdgePreservingDecomposition.cc cplx_wavelet_dec.cc FTblockDN.cc
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PF_correct_RT.cc
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dirpyrLab_denoise.cc dirpyr_equalizer.cc
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calc_distort.cc
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klt/convolve.cc klt/error.cc klt/klt.cc klt/klt_util.cc klt/pnmio.cc klt/pyramid.cc klt/selectGoodFeatures.cc
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klt/storeFeatures.cc klt/trackFeatures.cc klt/writeFeatures.cc
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)
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#FTblockDNchroma.cc
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add_library (rtengine ${RTENGINESOURCEFILES})
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#It may be nice to store library version too
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rtengine/FTblockDN.cc
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rtengine/FTblockDN.cc
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@ -0,0 +1,850 @@
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////////////////////////////////////////////////////////////////
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//
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// CFA denoise by wavelet transform, FT filtering
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//
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// copyright (c) 2008-2012 Emil Martinec <ejmartin@uchicago.edu>
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//
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//
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// code dated: March 9, 2012
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//
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// FTblockDN.cc 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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// This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
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//
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////////////////////////////////////////////////////////////////
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#include <math.h>
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#include <fftw3.h>
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//#include "bilateral2.h"
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#include "gauss.h"
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#include "rtengine.h"
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#include "improcfun.h"
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#include "LUT.h"
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#include "array2D.h"
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#include "iccmatrices.h"
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#include "boxblur.h"
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#ifdef _OPENMP
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#include <omp.h>
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#endif
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#include "cplx_wavelet_dec.h"
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#define SQR(x) ((x)*(x))
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//#define MIN(a,b) ((a) < (b) ? (a) : (b))
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//#define MAX(a,b) ((a) > (b) ? (a) : (b))
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//#define LIM(x,min,max) MAX(min,MIN(x,max))
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//#define ULIM(x,y,z) ((y) < (z) ? LIM(x,y,z) : LIM(x,z,y))
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//#define CLIP(x) LIM(x,0,65535)
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#define TS 64 // Tile size
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#define offset 25 // shift between tiles
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#define fTS ((TS/2+1)) // second dimension of Fourier tiles
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#define blkrad 1 // radius of block averaging
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#define epsilon 0.001f/(TS*TS) //tolerance
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namespace rtengine {
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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/*
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Structure of the algorithm:
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1. Compute an initial denoise of the image via undecimated wavelet transform
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and universal thresholding modulated by user input.
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2. Decompose the residual image into TSxTS size tiles, shifting by 'offset' each step
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(so roughly each pixel is in (TS/offset)^2 tiles); Discrete Cosine transform the tiles.
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3. Filter the DCT data to pick out patterns missed by the wavelet denoise
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4. Inverse DCT the denoised tile data and combine the tiles into a denoised output image.
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*/
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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void ImProcFunctions::RGB_denoise(Imagefloat * src, Imagefloat * dst, const procparams::DirPyrDenoiseParams & dnparams, const procparams::DefringeParams & defringe)
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{
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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/*if (plistener) {
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plistener->setProgressStr ("Denoise...");
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plistener->setProgress (0.0);
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}*/
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volatile double progress = 0.0;
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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const short int imheight=src->height, imwidth=src->width;
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if (dnparams.luma==0 && dnparams.chroma==0) {//nothing to do; copy src to dst
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for (int i=0; i<imheight; i++) {
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for (int j=0; j<imwidth; j++) {
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dst->r[i][j] = src->r[i][j];
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dst->r[i][j] = src->r[i][j];
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dst->r[i][j] = src->r[i][j];
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}
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}
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return;
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// gamma transform for input data
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float gam = dnparams.gamma;
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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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for (int i=0; i<65536; i++) {
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gamcurve[i] = (gamma((double)i/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)) * 32768.0f;
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}
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// inverse gamma transform for output data
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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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LUTf igamcurve(65536,0);
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for (int i=0; i<65536; i++) {
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igamcurve[i] = (gamma((float)i/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//srand((unsigned)time(0));//test with random data
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const float gain = pow (2.0, dnparams.expcomp);
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float noisevar_Ldetail = SQR((100-dnparams.Ldetail) * TS * 100.0f);
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array2D<float> tilemask_in(TS,TS);
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array2D<float> tilemask_out(TS,TS);
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const int border = MAX(2,TS/16);
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for (int i=0; i<TS; i++) {
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float i1 = abs((i>TS/2 ? i-TS+1 : i));
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float vmask = (i1<border ? SQR(sin((M_PI*i1)/(2*border))) : 1.0f);
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float vmask2 = (i1<2*border ? SQR(sin((M_PI*i1)/(2*border))) : 1.0f);
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for (int j=0; j<TS; j++) {
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float j1 = abs((j>TS/2 ? j-TS+1 : j));
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tilemask_in[i][j] = (vmask * (j1<border ? SQR(sin((M_PI*j1)/(2*border))) : 1.0f)) + epsilon;
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tilemask_out[i][j] = (vmask2 * (j1<2*border ? SQR(sin((M_PI*j1)/(2*border))) : 1.0f)) + epsilon;
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}
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}
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// begin block processing of image
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//output buffer
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Imagefloat * dsttmp = new Imagefloat(imwidth,imheight);
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for (int n=0; n<3*imwidth*imheight; n++) {
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dsttmp->data[n] = 0;
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}
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const int tilesize = 1024;
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const int overlap = 128;
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int numtiles_W, numtiles_H, tilewidth, tileheight, tileWskip, tileHskip;
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if (imwidth<tilesize) {
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numtiles_W = 1;
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tileWskip = imwidth;
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tilewidth = imwidth;
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} else {
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numtiles_W = ceil(((float)(imwidth))/(tilesize-overlap));
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tilewidth = ceil(((float)(imwidth))/(numtiles_W))+overlap;
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tilewidth += (tilewidth&1);
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tileWskip = tilewidth-overlap;
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}
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if (imheight<tilesize) {
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numtiles_H = 1;
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tileHskip = imheight;
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tileheight = imheight;
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} else {
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numtiles_H = ceil(((float)(imheight))/(tilesize-overlap));
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tileheight = ceil(((float)(imheight))/(numtiles_H))+overlap;
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tileheight += (tileheight&1);
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tileHskip = tileheight-overlap;
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}
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#pragma omp parallel for schedule(dynamic)
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for (int tiletop=0; tiletop<imheight; tiletop+=tileHskip) {
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for (int tileleft=0; tileleft<imwidth; tileleft+=tileWskip) {
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int tileright = MIN(imwidth,tileleft+tilewidth);
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int tilebottom = MIN(imheight,tiletop+tileheight);
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int width = tileright-tileleft;
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int height = tilebottom-tiletop;
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//LabImage * labin = new LabImage(width,height);
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LabImage * labdn = new LabImage(width,height);
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array2D<float> Ldetail(width,height);
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#ifdef _OPENMP
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#pragma omp parallel for
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#endif
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//fill tile from image
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for (int i=tiletop, i1=0; i<tilebottom; i++, i1++)
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for (int j=tileleft, j1=0; j<tileright; j++, j1++) {
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float X = gain*src->r[i][j];//xyz_prophoto[0][0]*src->r[i][j] + xyz_prophoto[0][1]*src->g[i][j] + xyz_prophoto[0][2]*src->b[i][j];
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float Y = gain*src->g[i][j];//xyz_prophoto[1][0]*src->r[i][j] + xyz_prophoto[1][1]*src->g[i][j] + xyz_prophoto[1][2]*src->b[i][j];
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float Z = gain*src->b[i][j];//xyz_prophoto[2][0]*src->r[i][j] + xyz_prophoto[2][1]*src->g[i][j] + xyz_prophoto[2][2]*src->b[i][j];
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X = X<65535.0f ? gamcurve[X] : (gamma((double)X/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
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Y = Y<65535.0f ? gamcurve[Y] : (gamma((double)Y/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
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Z = Z<65535.0f ? gamcurve[Z] : (gamma((double)Z/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
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labdn->L[i1][j1] = Y;
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labdn->a[i1][j1] = (X-Y);
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labdn->b[i1][j1] = (Y-Z);
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Ldetail[i1][j1] = 0;
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}
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array2D<float> Lin(width,height);
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float * Linptr = Lin;
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memcpy (Linptr, labdn->data, width*height*sizeof(float));
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//initial impulse denoise
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impulse_nr (labdn, 50.0f/20.0f);
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int datalen = labdn->W * labdn->H;
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//now perform basic wavelet denoise
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//last two arguments of wavelet decomposition are max number of wavelet decomposition levels;
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//and whether to subsample the image after wavelet filtering. Subsampling is coded as
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//binary 1 or 0 for each level, eg subsampling = 0 means no subsampling, 1 means subsample
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//the first level only, 7 means subsample the first three levels, etc.
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wavelet_decomposition Ldecomp(labdn->data, labdn->W, labdn->H, 5/*maxlevels*/, 0/*subsampling*/ );
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wavelet_decomposition adecomp(labdn->data+datalen, labdn->W, labdn->H, 5, 1 );
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wavelet_decomposition bdecomp(labdn->data+2*datalen, labdn->W, labdn->H, 5, 1 );
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float noisevarL = SQR(dnparams.luma/25.0f);
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float noisevarab = SQR(dnparams.chroma/10.0f);
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WaveletDenoiseAll_BiShrink(Ldecomp, adecomp, bdecomp, noisevarL, noisevarab);
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Ldecomp.reconstruct(labdn->data);
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adecomp.reconstruct(labdn->data+datalen);
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bdecomp.reconstruct(labdn->data+2*datalen);
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//TODO: at this point wavelet coefficients storage can be freed
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//second impulse denoise
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impulse_nr (labdn, 50.0f/20.0f);
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//PF_correct_RT(dst, dst, defringe.radius, defringe.threshold);
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array2D<float> Lwavdn(width,height,ARRAY2D_CLEAR_DATA);
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float * Lwavdnptr = Lwavdn;
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memcpy (Lwavdnptr, labdn->data, width*height*sizeof(float));
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// now do detail recovery using block DCT to detect patterns
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// missed by wavelet denoise
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// blocks are not the same thing as tiles!
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array2D<float> totwt(width,height,ARRAY2D_CLEAR_DATA);//weight for combining blocks
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// allocate DCT data structures
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// calculation for detail recovery blocks
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const int numblox_W = ceil(((float)(width))/(offset))+2*blkrad;
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const int numblox_H = ceil(((float)(height))/(offset))+2*blkrad;
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//const int nrtiles = numblox_W*numblox_H;
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// end of tiling calc
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float * Lblox = (float *) fftwf_malloc (numblox_W*TS*TS * sizeof (float));
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float * fLblox = (float *) fftwf_malloc (numblox_W*TS*TS * sizeof (float));
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//make a plan for FFTW
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fftwf_plan plan_forward_blox, plan_backward_blox;
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int nfwd[2]={TS,TS};
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//for DCT:
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const fftw_r2r_kind fwdkind[2] = {FFTW_REDFT10, FFTW_REDFT10};
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const fftw_r2r_kind bwdkind[2] = {FFTW_REDFT01, FFTW_REDFT01};
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plan_forward_blox = fftwf_plan_many_r2r(2, nfwd, numblox_W, Lblox, NULL, 1, TS*TS, fLblox, NULL, 1, TS*TS, fwdkind, FFTW_ESTIMATE );
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plan_backward_blox = fftwf_plan_many_r2r(2, nfwd, numblox_W, fLblox, NULL, 1, TS*TS, Lblox, NULL, 1, TS*TS, bwdkind, FFTW_ESTIMATE );
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// Main detail recovery algorithm: Block loop
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#pragma omp parallel for schedule(dynamic)
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for (int vblk=0; vblk<numblox_H; vblk++) {
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//printf("vblock=%d",vblk);
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int vblkmod = vblk%8;
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int top = (vblk-blkrad)*offset;
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float * buffer = new float [width + TS + 2*blkrad*offset];
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float * datarow = buffer+blkrad*offset;
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for (int i=0, row=top; i<TS; i++, row++) {
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int rr = row;
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if (row<0) {
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rr = MIN(-row,height-1);
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} else if (row>=height) {
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rr = MAX(0,2*height-2-row);
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}
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for (int j=0; j<labdn->W; j++) {
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datarow[j] = (Lin[rr][j]-Lwavdn[rr][j]);
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}
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for (int j=-blkrad*offset; j<0; j++) {
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datarow[j] = datarow[MIN(-j,width-1)];
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}
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for (int j=width; j<width+(TS-(width%TS)-1)+blkrad*offset; j++) {
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datarow[j] = datarow[MAX(0,2*width-2-j)];
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}//now we have a padded data row
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//now fill this row of the tiles with Lab high pass data
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for (int hblk=0; hblk<numblox_W; hblk++) {
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int left = (hblk-blkrad)*offset;
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int indx = (hblk)*TS;//index of block in malloc
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for (int j=0; j<TS; j++) {
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Lblox[(indx + i)*TS+j] = tilemask_in[i][j]*datarow[left+j];// luma data
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if (top+i>=0 && top+i<height && left+j>=0 && left+j<width) {
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totwt[top+i][left+j] += tilemask_in[i][j]*tilemask_out[i][j];
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}
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}
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}
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}//end of filling block row
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delete[] buffer;
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//fftwf_print_plan (plan_forward_blox);
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fftwf_execute_r2r(plan_forward_blox,Lblox,fLblox); // DCT an entire row of tiles
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// now process the vblk row of tiles for noise reduction
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for (int hblk=0; hblk<numblox_W; hblk++) {
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RGBtile_denoise (fLblox, vblk, hblk, numblox_H, numblox_W, noisevar_Ldetail );
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}//end of horizontal tile loop
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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//now perform inverse FT of an entire row of tiles
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fftwf_execute_r2r(plan_backward_blox,fLblox,Lblox); //for DCT
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int topproc = (vblk-blkrad)*offset;
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//add row of tiles to output image
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RGBoutput_tile_row (Lblox, Ldetail, tilemask_out, height, width, topproc );
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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}//end of vertical tile loop
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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// clean up
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//#pragma omp single nowait
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fftwf_destroy_plan( plan_forward_blox );
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//#pragma omp single nowait
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fftwf_destroy_plan( plan_backward_blox );
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fftwf_free ( Lblox);
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fftwf_free ( fLblox);
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//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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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//may want to include masking threshold for large hipass data to preserve edges/detail
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float hpdn = Ldetail[i][j]/totwt[i][j];//note that labdn initially stores the denoised hipass data
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|
||||
labdn->L[i][j] = Lwavdn[i][j] + hpdn;
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
// transform denoised "Lab" to output RGB
|
||||
|
||||
float * Vmask = new float [height];
|
||||
float * Hmask = new float [width];
|
||||
|
||||
for (int i=0; i<height; i++) {
|
||||
Vmask[i] = 1;
|
||||
}
|
||||
for (int j=0; j<width; j++) {
|
||||
Hmask[j] = 1;
|
||||
}
|
||||
for (int i=0; i<overlap; i++) {
|
||||
float mask = SQR(sin((M_PI*i)/(2*overlap)));
|
||||
if (tiletop>0) Vmask[i] = mask;
|
||||
if (tilebottom<imheight) Vmask[height-1-i] = mask;
|
||||
if (tileleft>0) Hmask[i] = mask;
|
||||
if (tileright<imwidth) Hmask[width-1-i] = mask;
|
||||
}
|
||||
|
||||
|
||||
#ifdef _OPENMP
|
||||
#pragma omp parallel for
|
||||
#endif
|
||||
for (int i=tiletop, i1=0; i<tilebottom; i++, i1++) {
|
||||
float X,Y,Z;
|
||||
for (int j=tileleft, j1=0; j<tileright; j++, j1++) {
|
||||
|
||||
Y = labdn->L[i1][j1];
|
||||
X = (labdn->a[i1][j1]) + Y;
|
||||
Z = Y - (labdn->b[i1][j1]);
|
||||
|
||||
X = X<32768.0f ? igamcurve[X] : (gamma((float)X/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
|
||||
Y = Y<32768.0f ? igamcurve[Y] : (gamma((float)Y/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
|
||||
Z = Z<32768.0f ? igamcurve[Z] : (gamma((float)Z/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
|
||||
|
||||
//Y = 65535.0f*(0.05+0.1*((float)rand()/(float)RAND_MAX));//test with random data
|
||||
|
||||
float mask = Vmask[i1]*Hmask[j1];
|
||||
|
||||
if (Y<-500) {
|
||||
float xxx=Y;
|
||||
}
|
||||
|
||||
dsttmp->r[i][j] += mask*X/gain;//prophoto_xyz[0][0]*X + prophoto_xyz[0][1]*Y + prophoto_xyz[0][2]*Z;
|
||||
dsttmp->g[i][j] += mask*Y/gain;//prophoto_xyz[1][0]*X + prophoto_xyz[1][1]*Y + prophoto_xyz[1][2]*Z;
|
||||
dsttmp->b[i][j] += mask*Z/gain;//prophoto_xyz[2][0]*X + prophoto_xyz[2][1]*Y + prophoto_xyz[2][2]*Z;
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
//delete labin;
|
||||
delete labdn;
|
||||
|
||||
|
||||
}//end of tile row
|
||||
}//end of tile loop
|
||||
|
||||
|
||||
//copy denoised image to output
|
||||
memcpy (dst->data, dsttmp->data, 3*imwidth*imheight*sizeof(float));
|
||||
|
||||
delete dsttmp;
|
||||
|
||||
}//end of main RGB_denoise
|
||||
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
|
||||
|
||||
void ImProcFunctions::RGBtile_denoise (float * fLblox, int vblproc, int hblproc, int numblox_H, int numblox_W, float noisevar_Ldetail ) //for DCT
|
||||
{
|
||||
float * nbrwt = new float[TS*TS]; //for DCT
|
||||
|
||||
int blkstart = hblproc*TS*TS;
|
||||
|
||||
boxabsblur(fLblox+blkstart, nbrwt, 3, 3, TS, TS);//blur neighbor weights for more robust estimation //for DCT
|
||||
|
||||
for (int n=0; n<TS*TS; n++) { //for DCT
|
||||
fLblox[blkstart+n] *= (1-expf(-SQR(nbrwt[n])/noisevar_Ldetail));
|
||||
}//output neighbor averaged result
|
||||
|
||||
delete[] nbrwt;
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//printf("vblk=%d hlk=%d wsqave=%f || ",vblproc,hblproc,wsqave);
|
||||
|
||||
}//end of function tile_denoise
|
||||
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
void ImProcFunctions::RGBoutput_tile_row (float *bloxrow_L, float ** Ldetail, float ** tilemask_out, int height, int width, int top )
|
||||
{
|
||||
const int numblox_W = ceil(((float)(width))/(offset));
|
||||
const float DCTnorm = 1.0f/(4*TS*TS); //for DCT
|
||||
|
||||
//add row of tiles to output image
|
||||
for (int hblk=0; hblk < numblox_W; hblk++) {
|
||||
int left = (hblk-blkrad)*offset;
|
||||
int bottom = MIN( top+TS,height);
|
||||
int right = MIN(left+TS, width);
|
||||
int imin = MAX(0,-top);
|
||||
int jmin = MAX(0,-left);
|
||||
int imax = bottom - top;
|
||||
int jmax = right - left;
|
||||
|
||||
int indx = hblk*TS;
|
||||
|
||||
for (int i=imin; i<imax; i++)
|
||||
for (int j=jmin; j<jmax; j++) {
|
||||
|
||||
Ldetail[top+i][left+j] += tilemask_out[i][j]*bloxrow_L[(indx + i)*TS+j]*DCTnorm; //for DCT
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
#undef TS
|
||||
#undef fTS
|
||||
#undef offset
|
||||
#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_)/((float)(count-count_)) )/0.6745);
|
||||
|
||||
}
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
|
||||
void ImProcFunctions::WaveletDenoiseAll_BiShrink(wavelet_decomposition &WaveletCoeffs_L, wavelet_decomposition &WaveletCoeffs_a,
|
||||
wavelet_decomposition &WaveletCoeffs_b, float noisevar_L, float noisevar_ab )
|
||||
{
|
||||
int maxlvl = WaveletCoeffs_L.maxlevel();
|
||||
const float eps = 0.01f;
|
||||
int max;
|
||||
float parfrac = 0.05;
|
||||
|
||||
float madL[8][3], mada[8][3], madb[8][3];
|
||||
|
||||
for (int lvl=0; lvl<maxlvl; lvl++) {
|
||||
// compute median absolute deviation (MAD) of detail coefficients as robust noise estimator
|
||||
|
||||
int Wlvl_L = WaveletCoeffs_L.level_W(lvl);
|
||||
int Hlvl_L = WaveletCoeffs_L.level_H(lvl);
|
||||
|
||||
int Wlvl_ab = WaveletCoeffs_a.level_W(lvl);
|
||||
int Hlvl_ab = WaveletCoeffs_a.level_H(lvl);
|
||||
|
||||
float ** WavCoeffs_L = WaveletCoeffs_L.level_coeffs(lvl);
|
||||
float ** WavCoeffs_a = WaveletCoeffs_a.level_coeffs(lvl);
|
||||
float ** WavCoeffs_b = WaveletCoeffs_b.level_coeffs(lvl);
|
||||
|
||||
for (int dir=1; dir<4; dir++) {
|
||||
madL[lvl][dir-1] = SQR(MadMax(WavCoeffs_L[dir], max, Wlvl_L*Hlvl_L));
|
||||
mada[lvl][dir-1] = SQR(MadMax(WavCoeffs_a[dir], max, Wlvl_ab*Hlvl_ab));
|
||||
madb[lvl][dir-1] = SQR(MadMax(WavCoeffs_b[dir], max, Wlvl_ab*Hlvl_ab));
|
||||
}
|
||||
}
|
||||
|
||||
for (int lvl=maxlvl-1; lvl>=0; lvl--) {//for levels less than max, use level diff to make edge mask
|
||||
//for (int lvl=0; lvl<maxlvl; lvl++) {
|
||||
|
||||
int Wlvl_L = WaveletCoeffs_L.level_W(lvl);
|
||||
int Hlvl_L = WaveletCoeffs_L.level_H(lvl);
|
||||
|
||||
int Wlvl_ab = WaveletCoeffs_a.level_W(lvl);
|
||||
int Hlvl_ab = WaveletCoeffs_a.level_H(lvl);
|
||||
|
||||
float skip_L = WaveletCoeffs_L.level_stride(lvl);
|
||||
float skip_ab = WaveletCoeffs_a.level_stride(lvl);
|
||||
|
||||
float ** WavCoeffs_L = WaveletCoeffs_L.level_coeffs(lvl);
|
||||
float ** WavCoeffs_a = WaveletCoeffs_a.level_coeffs(lvl);
|
||||
float ** WavCoeffs_b = WaveletCoeffs_b.level_coeffs(lvl);
|
||||
|
||||
if (lvl==maxlvl-1) {
|
||||
ShrinkAll(WavCoeffs_L, WavCoeffs_a, WavCoeffs_b, lvl, Wlvl_L, Hlvl_L, Wlvl_ab, Hlvl_ab,
|
||||
skip_L, skip_ab, noisevar_L, noisevar_ab);//TODO: this implies redundant evaluation of MAD
|
||||
} else {
|
||||
|
||||
float ** WavPars_L = WaveletCoeffs_L.level_coeffs(lvl+1);
|
||||
//float ** WavPars_a = WaveletCoeffs_a.level_coeffs(lvl+1);
|
||||
//float ** WavPars_b = WaveletCoeffs_b.level_coeffs(lvl+1);
|
||||
|
||||
//simple wavelet shrinkage
|
||||
float * sfave = new float[Wlvl_L*Hlvl_L];
|
||||
array2D<float> edge(Wlvl_L,Hlvl_L);
|
||||
AlignedBuffer<double>* buffer = new AlignedBuffer<double> (MAX(Wlvl_L,Hlvl_L));
|
||||
|
||||
printf("\n level=%d \n",lvl);
|
||||
|
||||
for (int dir=1; dir<4; dir++) {
|
||||
float mad_L = madL[lvl][dir-1];
|
||||
float mad_a = noisevar_ab*mada[lvl][dir-1];
|
||||
float mad_b = noisevar_ab*madb[lvl][dir-1];
|
||||
//float mad_Lpar = madL[lvl+1][dir-1];
|
||||
//float mad_apar = mada[lvl+1][dir-1];
|
||||
//float mad_bpar = mada[lvl+1][dir-1];
|
||||
|
||||
//float skip_ab_ratio = WaveletCoeffs_a.level_stride(lvl+1)/skip_ab;
|
||||
float skip_L_ratio = WaveletCoeffs_L.level_stride(lvl+1)/skip_L;
|
||||
|
||||
if (noisevar_ab>0.01) {
|
||||
|
||||
printf(" dir=%d mad_L=%f mad_a=%f mad_b=%f \n",dir,sqrt(mad_L),sqrt(mad_a),sqrt(mad_b));
|
||||
|
||||
for (int i=0; i<Hlvl_ab; i++) {
|
||||
for (int j=0; j<Wlvl_ab; j++) {
|
||||
|
||||
int coeffloc_ab = i*Wlvl_ab+j;
|
||||
//int coeffloc_abpar = (MAX(0,i-skip_ab)*Wlvl_ab+MAX(0,j-skip_ab))/skip_ab_ratio;
|
||||
|
||||
int coeffloc_L = ((i*skip_L)/skip_ab)*Wlvl_L + ((j*skip_L)/skip_ab);
|
||||
|
||||
float mag_L = SQR(WavCoeffs_L[dir][coeffloc_L ])+eps;
|
||||
float mag_a = SQR(WavCoeffs_a[dir][coeffloc_ab])+eps;
|
||||
float mag_b = SQR(WavCoeffs_b[dir][coeffloc_ab])+eps;
|
||||
|
||||
//float edgefactor = 1-exp(-mag_L/(9*mad_L));// * exp(-mag_a/(4*mad_a)) * exp(-mag_b/(4*mad_b));
|
||||
|
||||
//float coeff_a = sqrt(SQR(WavCoeffs_a[dir][coeffloc_ab])/mad_a+SQR(parfrac*WavPars_a[dir][coeffloc_abpar])/mad_apar);
|
||||
//float coeff_b = sqrt(SQR(WavCoeffs_b[dir][coeffloc_ab])/mad_b+SQR(parfrac*WavPars_b[dir][coeffloc_abpar])/mad_bpar);
|
||||
|
||||
// 'firm' threshold of chroma coefficients
|
||||
//WavCoeffs_a[dir][coeffloc_ab] *= edgefactor*(coeff_a>2 ? 1 : (coeff_a<1 ? 0 : (coeff_a - 1)));
|
||||
//WavCoeffs_b[dir][coeffloc_ab] *= edgefactor*(coeff_b>2 ? 1 : (coeff_b<1 ? 0 : (coeff_b - 1)));
|
||||
|
||||
//float satfactor_a = mad_a/(mad_a+0.5*SQR(WavCoeffs_a[0][coeffloc_ab]));
|
||||
//float satfactor_b = mad_b/(mad_b+0.5*SQR(WavCoeffs_b[0][coeffloc_ab]));
|
||||
|
||||
WavCoeffs_a[dir][coeffloc_ab] *= SQR(1-exp(-(mag_a/mad_a)-(mag_L/(9*mad_L)))/*satfactor_a*/);
|
||||
WavCoeffs_b[dir][coeffloc_ab] *= SQR(1-exp(-(mag_b/mad_b)-(mag_L/(9*mad_L)))/*satfactor_b*/);
|
||||
|
||||
}
|
||||
}//now chrominance coefficients are denoised
|
||||
}
|
||||
|
||||
if (noisevar_L>0.01) {
|
||||
mad_L *= noisevar_L*5/(lvl+1);
|
||||
|
||||
for (int i=0; i<Hlvl_L; i++)
|
||||
for (int j=0; j<Wlvl_L; j++) {
|
||||
|
||||
int coeffloc_L = i*Wlvl_L+j;
|
||||
int coeffloc_Lpar = (MAX(0,i-skip_L)*Wlvl_L+MAX(0,j-skip_L))/skip_L_ratio;
|
||||
|
||||
float mag_L = SQR(WavCoeffs_L[dir][coeffloc_L]);
|
||||
//float mag_Lpar = SQR(parfrac*WavPars_L[dir][coeffloc_Lpar]);
|
||||
//float sf_L = SQR(1-expf(-(mag_L/mad_L)-(mag_Lpar/mad_L)));
|
||||
float sf_L = mag_L/(mag_L+mad_L*exp(-mag_L/(9*mad_L))+eps);
|
||||
|
||||
sfave[coeffloc_L] = sf_L;
|
||||
|
||||
edge[i][j] = (WavCoeffs_L[dir][coeffloc_L] - WavPars_L[dir][coeffloc_Lpar]);
|
||||
}
|
||||
|
||||
//blur edge measure
|
||||
gaussHorizontal<float> (edge, edge, buffer, Wlvl_L, Hlvl_L, 1<<(lvl+1), false /*multiThread*/);
|
||||
gaussVertical<float> (edge, edge, buffer, Wlvl_L, Hlvl_L, 1<<(lvl+1), false);
|
||||
|
||||
boxblur(sfave, sfave, lvl+2, lvl+2, Wlvl_L, Hlvl_L);//increase smoothness by locally averaging shrinkage
|
||||
|
||||
for (int i=0; i<Hlvl_L; i++)
|
||||
for (int j=0; j<Wlvl_L; j++) {
|
||||
|
||||
int coeffloc_L = i*Wlvl_L+j;
|
||||
|
||||
float mag_L = SQR(WavCoeffs_L[dir][coeffloc_L]);
|
||||
//float sf_L = SQR(1-expf(-(mag_L/mad_L)-(mag_Lpar/mad_L)));
|
||||
|
||||
float edgefactor = 1;//expf(-SQR(edge[i][j])/mad_L);
|
||||
|
||||
float sf_L = mag_L/(mag_L + edgefactor*mad_L*exp(-mag_L/(9*mad_L))+eps);
|
||||
|
||||
//use smoothed shrinkage unless local shrinkage is much less
|
||||
WavCoeffs_L[dir][coeffloc_L] *= (SQR(edgefactor*sfave[coeffloc_L])+SQR(sf_L))/(edgefactor*sfave[coeffloc_L]+sf_L+eps);
|
||||
|
||||
}//now luminance coeffs are denoised
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
delete[] sfave;
|
||||
delete buffer;
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
|
||||
void ImProcFunctions::ShrinkAll(float ** WavCoeffs_L, float ** WavCoeffs_a, float ** WavCoeffs_b, int level,
|
||||
int W_L, int H_L, int W_ab, int H_ab, int skip_L, int skip_ab, float noisevar_L, float noisevar_ab)
|
||||
{
|
||||
//simple wavelet shrinkage
|
||||
const float eps = 0.01f;
|
||||
float * sfave = new float[W_L*H_L];
|
||||
int max;
|
||||
|
||||
printf("\n level=%d \n",level);
|
||||
|
||||
for (int dir=1; dir<4; dir++) {
|
||||
float madL = SQR(MadMax(WavCoeffs_L[dir], max, W_L*H_L));
|
||||
float mada = SQR(MadMax(WavCoeffs_a[dir], max, W_ab*H_ab));
|
||||
float madb = SQR(MadMax(WavCoeffs_b[dir], max, W_ab*H_ab));
|
||||
|
||||
//float thresh_L = sqrt(mad_L*noisevar_L);
|
||||
//float thresh_a = sqrt(mad_a*noisevar_ab);
|
||||
//float thresh_b = sqrt(mad_b*noisevar_ab);
|
||||
|
||||
printf(" dir=%d mad_L=%f mad_a=%f mad_b=%f \n",dir,sqrt(madL),sqrt(mada),sqrt(madb));
|
||||
|
||||
//float mad_L = noisevar_L *6/((level+2)*pow(2.0f,level));
|
||||
//float mad_a = noisevar_ab;
|
||||
//float mad_b = noisevar_ab;
|
||||
float mad_L = madL*noisevar_L *6/(level+2);
|
||||
float mad_a = mada*noisevar_ab;
|
||||
float mad_b = madb*noisevar_ab;
|
||||
|
||||
if (noisevar_ab>0.01) {
|
||||
for (int i=0; i<H_ab; i++) {
|
||||
for (int j=0; j<W_ab; j++) {
|
||||
|
||||
int coeffloc_ab = i*W_ab+j;
|
||||
int coeffloc_L = ((i*skip_L)/skip_ab)*W_L + ((j*skip_L)/skip_ab);
|
||||
|
||||
float mag_L = SQR(WavCoeffs_L[dir][coeffloc_L ])+eps;
|
||||
float mag_a = SQR(WavCoeffs_a[dir][coeffloc_ab])+eps;
|
||||
float mag_b = SQR(WavCoeffs_b[dir][coeffloc_ab])+eps;
|
||||
|
||||
//float edgefactor = exp(-mag_L/(3*mad_L))) * exp(-mag_a/(3*mad_a)) * exp(-mag_b/(3*mad_b));
|
||||
//float edgefactor = 1-exp(-mag_L/(9*mad_L));
|
||||
|
||||
//WavCoeffs_a[dir][coeffloc_ab] *= mag_a/(mag_a + noisevar_ab*mad_a*edgefactor + eps);
|
||||
//WavCoeffs_b[dir][coeffloc_ab] *= mag_b/(mag_b + noisevar_ab*mad_b*edgefactor + eps);
|
||||
|
||||
//float coeff_a = fabs(WavCoeffs_a[dir][coeffloc_ab]);
|
||||
//float coeff_b = fabs(WavCoeffs_b[dir][coeffloc_ab]);
|
||||
|
||||
// 'firm' threshold of chroma coefficients
|
||||
WavCoeffs_a[dir][coeffloc_ab] *= SQR(1-exp(-(mag_a/mad_a)-(mag_L/(9*madL))));//(coeff_a>2*thresh_a ? 1 : (coeff_a<thresh_a ? 0 : (coeff_a/thresh_a - 1)));
|
||||
WavCoeffs_b[dir][coeffloc_ab] *= SQR(1-exp(-(mag_b/mad_b)-(mag_L/(9*madL))));//(coeff_b>2*thresh_b ? 1 : (coeff_b<thresh_b ? 0 : (coeff_b/thresh_b - 1)));
|
||||
|
||||
//WavCoeffs_b[dir][coeffloc_ab] *= (fabs(WavCoeffs_b[dir][coeffloc_ab])<thresh_a*noise_ab ? 0 : 1);
|
||||
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (noisevar_L>0.01) {
|
||||
|
||||
for (int i=0; i<W_L*H_L; i++) {
|
||||
|
||||
//float coeff_L = fabs(WavCoeffs_L[dir][i]);
|
||||
// 'firm' threshold of luma coefficients
|
||||
//float shrinkfactor = (coeff_L>2*thresh_L ? 1 : (coeff_L<thresh_L ? 0 : (coeff_L/thresh_L - 1)));
|
||||
|
||||
float mag = SQR(WavCoeffs_L[dir][i]);
|
||||
float shrinkfactor = mag/(mag+mad_L*exp(-mag/(9*mad_L))+eps);
|
||||
//float shrinkfactor = SQR(1-exp(-(mag/(mad_L))));
|
||||
|
||||
//float shrinkfactor = mag/(mag+noisevar*SQR(sfave[coeffloc])+eps);
|
||||
|
||||
//WavCoeffs_L[dir][i] *= shrinkfactor;
|
||||
sfave[i] = shrinkfactor;
|
||||
}
|
||||
|
||||
boxblur(sfave, sfave, level+2, level+2, W_L, H_L);//increase smoothness by locally averaging shrinkage
|
||||
for (int i=0; i<W_L*H_L; i++) {
|
||||
|
||||
//float coeff_L = fabs(WavCoeffs_L[dir][i]);
|
||||
// 'firm' threshold of chroma coefficients
|
||||
//float sf = (coeff_L>2*thresh_L ? 1 : (coeff_L<thresh_L ? 0 : (coeff_L/thresh_L - 1)));
|
||||
|
||||
float mag = SQR(WavCoeffs_L[dir][i]);
|
||||
float sf = mag/(mag+mad_L*exp(-mag/(9*mad_L))+eps);
|
||||
//float sf = SQR(1-exp(-(mag/(mad_L))));
|
||||
//float sf = mag/(mag+noisevar_L*mad_L);
|
||||
|
||||
//use smoothed shrinkage unless local shrinkage is much less
|
||||
WavCoeffs_L[dir][i] *= (SQR(sfave[i])+SQR(sf))/(sfave[i]+sf+eps);
|
||||
|
||||
}//now luminance coeffs are denoised
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
delete[] sfave;
|
||||
}
|
||||
|
||||
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
|
||||
};
|
||||
|
@ -233,8 +233,8 @@ namespace rtengine {
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
// TODO: begin block processing
|
||||
|
||||
/*const int tilesize = 1000;
|
||||
/*
|
||||
const int tilesize = 1000;
|
||||
const int overlap = 100;
|
||||
if (width>tilesize and height>tilesize) {
|
||||
const int numtiles_W = ceil(((float)(width))/(tilesize-overlap));
|
||||
@ -243,6 +243,17 @@ namespace rtengine {
|
||||
int tileheight = ceil(((float)(height))/(numtiles_H));
|
||||
tilewidth = tilewidth + (tilewidth&1);
|
||||
tileheight = tileheight + (tileheight&1);
|
||||
|
||||
for (int tiletop=0; tiletop<height; tiletop+=(tileheight-overlap)) {
|
||||
for (int tileleft=0; tileleft<width; tileleft+=(tilewidth-overlap)) {
|
||||
new
|
||||
//fill tile from image
|
||||
for (int i=0; int<tileheight; i++) {
|
||||
//do stuff
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}*/
|
||||
|
||||
LabImage * labin = new LabImage(width,height);
|
||||
|
@ -142,22 +142,22 @@ namespace rtengine {
|
||||
int pitch, int scale, const int luma, const int chroma/*, LUTf & Lcurve, LUTf & abcurve*/ );
|
||||
|
||||
// FT denoise
|
||||
void RGB_InputTransf(Imagefloat * src, LabImage * dst, const procparams::DirPyrDenoiseParams & dnparams, const procparams::DefringeParams & defringe);
|
||||
void RGB_OutputTransf(LabImage * src, Imagefloat * dst, const procparams::DirPyrDenoiseParams & dnparams);
|
||||
void output_tile_row (float *Lbloxrow, float ** Lhipassdn, float ** tilemask, int height, int width, int top, int blkrad );
|
||||
//void RGB_InputTransf(Imagefloat * src, LabImage * dst, const procparams::DirPyrDenoiseParams & dnparams, const procparams::DefringeParams & defringe);
|
||||
//void RGB_OutputTransf(LabImage * src, Imagefloat * dst, const procparams::DirPyrDenoiseParams & dnparams);
|
||||
//void output_tile_row (float *Lbloxrow, float ** Lhipassdn, float ** tilemask, int height, int width, int top, int blkrad );
|
||||
void RGB_denoise(Imagefloat * src, Imagefloat * dst, const procparams::DirPyrDenoiseParams & dnparams, const procparams::DefringeParams & defringe);
|
||||
void RGBtile_denoise (float ** fLblox, int vblproc, int hblproc, int numblox_H, int numblox_W, float noisevar_L ); //for DCT
|
||||
void RGBoutput_tile_row (float *Lbloxrow, LabImage * labdn, float ** tilemask_out, int height, int width, int top );
|
||||
void WaveletDenoise(cplx_wavelet_decomposition &DualTreeCoeffs, float noisevar );
|
||||
void WaveletDenoise(wavelet_decomposition &WaveletCoeffs, float noisevar );
|
||||
void WaveletDenoiseAll(wavelet_decomposition &WaveletCoeffs_L, wavelet_decomposition &WaveletCoeffs_a,
|
||||
wavelet_decomposition &WaveletCoeffs_b, float noisevar_L, float noisevar_ab );
|
||||
void RGBtile_denoise (float * fLblox, int vblproc, int hblproc, int numblox_H, int numblox_W, float noisevar_L ); //for DCT
|
||||
void RGBoutput_tile_row (float *Lbloxrow, float ** Ldetail, float ** tilemask_out, int height, int width, int top );
|
||||
//void WaveletDenoise(cplx_wavelet_decomposition &DualTreeCoeffs, float noisevar );
|
||||
//void WaveletDenoise(wavelet_decomposition &WaveletCoeffs, float noisevar );
|
||||
//void WaveletDenoiseAll(wavelet_decomposition &WaveletCoeffs_L, wavelet_decomposition &WaveletCoeffs_a,
|
||||
// wavelet_decomposition &WaveletCoeffs_b, float noisevar_L, float noisevar_ab );
|
||||
void WaveletDenoiseAll_BiShrink(wavelet_decomposition &WaveletCoeffs_L, wavelet_decomposition &WaveletCoeffs_a,
|
||||
wavelet_decomposition &WaveletCoeffs_b, float noisevar_L, float noisevar_ab );
|
||||
void BiShrink(float * ReCoeffs, float * ImCoeffs, float * ReParents, float * ImParents, \
|
||||
int W, int H, int level, int padding, float noisevar);
|
||||
void Shrink(float ** WavCoeffs, int W, int H, int level, float noisevar);
|
||||
void ShrinkAll(float ** WavCoeffs_L, float ** WavCoeffs_a, float ** WavCoeffs_b, int level, \
|
||||
//void BiShrink(float * ReCoeffs, float * ImCoeffs, float * ReParents, float * ImParents,
|
||||
// int W, int H, int level, int padding, float noisevar);
|
||||
//void Shrink(float ** WavCoeffs, int W, int H, int level, float noisevar);
|
||||
void ShrinkAll(float ** WavCoeffs_L, float ** WavCoeffs_a, float ** WavCoeffs_b, int level,
|
||||
int W_L, int H_L, int W_ab, int H_ab, int skip_L, int skip_ab, float noisevar_L, float noisevar_ab);
|
||||
float MadMax(float * HH_Coeffs, int &max, int datalen);
|
||||
|
||||
|
@ -111,10 +111,6 @@ IImage16* processImage (ProcessingJob* pjob, int& errorCode, ProgressListener* p
|
||||
imgsrc->getImage (currWB, tr, baseImg, pp, params.hlrecovery, params.icm, params.raw);
|
||||
if (pl) pl->setProgress (0.45);
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
// start tile processing...???
|
||||
|
||||
// perform luma denoise
|
||||
LabImage* labView = new LabImage (fw,fh);
|
||||
if (params.dirpyrDenoise.enabled) {
|
||||
@ -160,7 +156,7 @@ IImage16* processImage (ProcessingJob* pjob, int& errorCode, ProgressListener* p
|
||||
}
|
||||
|
||||
// at this stage, we can flush the raw data to free up quite an important amount of memory
|
||||
// commented out because it make the application crash when batch processing...
|
||||
// commented out because it makes the application crash when batch processing...
|
||||
// TODO: find a better place to flush rawData and rawRGB
|
||||
//imgsrc->flushRawData();
|
||||
//imgsrc->flushRGB();
|
||||
@ -194,6 +190,9 @@ IImage16* processImage (ProcessingJob* pjob, int& errorCode, ProgressListener* p
|
||||
if (pl)
|
||||
pl->setProgress (0.5);
|
||||
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
// start tile processing...???
|
||||
|
||||
// luminance histogram update
|
||||
hist16.clear();
|
||||
@ -237,6 +236,9 @@ IImage16* processImage (ProcessingJob* pjob, int& errorCode, ProgressListener* p
|
||||
// directional pyramid equalizer
|
||||
ipf.dirpyrequalizer (labView);//TODO: this is the luminance tonecurve, not the RGB one
|
||||
|
||||
// end tile processing...???
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
|
||||
|
||||
if (pl) pl->setProgress (0.60);
|
||||
|
||||
|
Loading…
x
Reference in New Issue
Block a user