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rawTherapee/rtengine/FTblockDN.cc

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////////////////////////////////////////////////////////////////
//
// CFA denoise by wavelet transform, FT filtering
//
// copyright (c) 2008-2012 Emil Martinec <ejmartin@uchicago.edu>
//
//
// code dated: March 9, 2012
//
// FTblockDN.cc is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
//
////////////////////////////////////////////////////////////////
#include <math.h>
#include <fftw3.h>
//#include "bilateral2.h"
#include "gauss.h"
#include "rtengine.h"
#include "improcfun.h"
#include "LUT.h"
#include "array2D.h"
#include "iccmatrices.h"
#include "boxblur.h"
#include "rt_math.h"
#ifdef _OPENMP
#include <omp.h>
#endif
#include "cplx_wavelet_dec.h"
//#define MIN(a,b) ((a) < (b) ? (a) : (b))
//#define MAX(a,b) ((a) > (b) ? (a) : (b))
//#define LIM(x,min,max) MAX(min,MIN(x,max))
//#define ULIM(x,y,z) ((y) < (z) ? LIM(x,y,z) : LIM(x,z,y))
//#define CLIP(x) LIM(x,0,65535)
#define TS 64 // Tile size
#define offset 25 // shift between tiles
#define fTS ((TS/2+1)) // second dimension of Fourier tiles
#define blkrad 1 // radius of block averaging
#define epsilon 0.001f/(TS*TS) //tolerance
namespace rtengine {
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*
Structure of the algorithm:
1. Compute an initial denoise of the image via undecimated wavelet transform
and universal thresholding modulated by user input.
2. Decompose the residual image into TSxTS size tiles, shifting by 'offset' each step
(so roughly each pixel is in (TS/offset)^2 tiles); Discrete Cosine transform the tiles.
3. Filter the DCT data to pick out patterns missed by the wavelet denoise
4. Inverse DCT the denoised tile data and combine the tiles into a denoised output image.
*/
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
void ImProcFunctions::RGB_denoise(Imagefloat * src, Imagefloat * dst, bool isRAW, const procparams::DirPyrDenoiseParams & dnparams, const procparams::DefringeParams & defringe)
{
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
/*if (plistener) {
plistener->setProgressStr ("Denoise...");
plistener->setProgress (0.0);
}*/
volatile double progress = 0.0;
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
const short int imheight=src->height, imwidth=src->width;
if (dnparams.luma==0 && dnparams.chroma==0) {
//nothing to do; copy src to dst
memcpy(dst->data,src->data,dst->width*dst->height*3*sizeof(float));
return;
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// gamma transform for input data
float gam = dnparams.gamma;
float gamthresh = 0.001;
float gamslope = exp(log((double)gamthresh)/gam)/gamthresh;
LUTf gamcurve(65536,0);
for (int i=0; i<65536; i++) {
gamcurve[i] = (Color::gamma((double)i/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)) * 32768.0f;
}
// inverse gamma transform for output data
float igam = 1/gam;
float igamthresh = gamthresh*gamslope;
float igamslope = 1/gamslope;
LUTf igamcurve(65536,0);
for (int i=0; i<65536; i++) {
igamcurve[i] = (Color::gamma((float)i/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//srand((unsigned)time(0));//test with random data
const float gain = pow (2.0, dnparams.expcomp);
float noisevar_Ldetail = SQR((SQR(100-dnparams.Ldetail) + 50*(100-dnparams.Ldetail)) * TS * 0.5f);
array2D<float> tilemask_in(TS,TS);
array2D<float> tilemask_out(TS,TS);
const int border = MAX(2,TS/16);
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i=0; i<TS; i++) {
float i1 = abs((i>TS/2 ? i-TS+1 : i));
float vmask = (i1<border ? SQR(sin((M_PI*i1)/(2*border))) : 1.0f);
float vmask2 = (i1<2*border ? SQR(sin((M_PI*i1)/(2*border))) : 1.0f);
for (int j=0; j<TS; j++) {
float j1 = abs((j>TS/2 ? j-TS+1 : j));
tilemask_in[i][j] = (vmask * (j1<border ? SQR(sin((M_PI*j1)/(2*border))) : 1.0f)) + epsilon;
tilemask_out[i][j] = (vmask2 * (j1<2*border ? SQR(sin((M_PI*j1)/(2*border))) : 1.0f)) + epsilon;
}
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// begin tile processing of image
//output buffer
Imagefloat * dsttmp = new Imagefloat(imwidth,imheight);
for (int n=0; n<3*imwidth*imheight; n++) dsttmp->data[n] = 0;
const int tilesize = 1024;
const int overlap = 128;
int numtiles_W, numtiles_H, tilewidth, tileheight, tileWskip, tileHskip;
if (imwidth<tilesize) {
numtiles_W = 1;
tileWskip = imwidth;
tilewidth = imwidth;
} else {
numtiles_W = ceil(((float)(imwidth))/(tilesize-overlap));
tilewidth = ceil(((float)(imwidth))/(numtiles_W))+overlap;
tilewidth += (tilewidth&1);
tileWskip = tilewidth-overlap;
}
if (imheight<tilesize) {
numtiles_H = 1;
tileHskip = imheight;
tileheight = imheight;
} else {
numtiles_H = ceil(((float)(imheight))/(tilesize-overlap));
tileheight = ceil(((float)(imheight))/(numtiles_H))+overlap;
tileheight += (tileheight&1);
tileHskip = tileheight-overlap;
}
//now we have tile dimensions, overlaps
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// According to FFTW-Doc 'it is safe to execute the same plan in parallel by multiple threads', so we now create 4 plans
// outside the parallel region and use them inside the parallel region.
// calculate max size of numblox_W.
int max_numblox_W = ceil(((float)(MIN(imwidth,tilewidth)))/(offset))+2*blkrad;
// calculate min size of numblox_W.
int min_numblox_W = ceil(((float)((MIN(imwidth,((numtiles_W - 1) * tileWskip) + tilewidth) ) - ((numtiles_W - 1) * tileWskip)))/(offset))+2*blkrad;
// these are needed only for creation of the plans and will be freed before entering the parallel loop
float * Lbloxtmp;
float * fLbloxtmp;
Lbloxtmp = (float*) fftwf_malloc(max_numblox_W*TS*TS*sizeof (float));
fLbloxtmp = (float*) fftwf_malloc(max_numblox_W*TS*TS*sizeof (float));
int nfwd[2]={TS,TS};
//for DCT:
const fftw_r2r_kind fwdkind[2] = {FFTW_REDFT10, FFTW_REDFT10};
const fftw_r2r_kind bwdkind[2] = {FFTW_REDFT01, FFTW_REDFT01};
fftwf_plan plan_forward_blox[2];
fftwf_plan plan_backward_blox[2];
// Creating the plans with FFTW_MEASURE instead of FFTW_ESTIMATE speeds up the execute a bit
plan_forward_blox[0] = fftwf_plan_many_r2r(2, nfwd, max_numblox_W, Lbloxtmp, NULL, 1, TS*TS, fLbloxtmp, NULL, 1, TS*TS, fwdkind, FFTW_MEASURE );
plan_backward_blox[0] = fftwf_plan_many_r2r(2, nfwd, max_numblox_W, fLbloxtmp, NULL, 1, TS*TS, Lbloxtmp, NULL, 1, TS*TS, bwdkind, FFTW_MEASURE );
plan_forward_blox[1] = fftwf_plan_many_r2r(2, nfwd, min_numblox_W, Lbloxtmp, NULL, 1, TS*TS, fLbloxtmp, NULL, 1, TS*TS, fwdkind, FFTW_MEASURE );
plan_backward_blox[1] = fftwf_plan_many_r2r(2, nfwd, min_numblox_W, fLbloxtmp, NULL, 1, TS*TS, Lbloxtmp, NULL, 1, TS*TS, bwdkind, FFTW_MEASURE );
fftwf_free ( Lbloxtmp );
fftwf_free ( fLbloxtmp );
#ifdef _OPENMP
// Calculate number of tiles. If less than omp_get_max_threads(), then limit num_threads to number of tiles
int numtiles = numtiles_W * numtiles_H;
int numthreads = MIN(numtiles,omp_get_max_threads());
//if(options.RgbDenoiseThreadLimit > 0) numthreads = MIN(numthreads,options.RgbDenoiseThreadLimit);
#pragma omp parallel num_threads(numthreads)
#endif
{
//DCT block data storage
float * Lblox;
float * fLblox;
#ifdef _OPENMP
#pragma omp critical
#endif
{
Lblox = (float*) fftwf_malloc(max_numblox_W*TS*TS*sizeof(float));
fLblox = (float*) fftwf_malloc(max_numblox_W*TS*TS*sizeof(float));
}
#ifdef _OPENMP
#pragma omp for schedule(dynamic) collapse(2)
#endif
for (int tiletop=0; tiletop<imheight; tiletop+=tileHskip) {
for (int tileleft=0; tileleft<imwidth; tileleft+=tileWskip) {
int tileright = MIN(imwidth,tileleft+tilewidth);
int tilebottom = MIN(imheight,tiletop+tileheight);
int width = tileright-tileleft;
int height = tilebottom-tiletop;
//input L channel
array2D<float> Lin(width,height);
//wavelet denoised image
LabImage * labdn = new LabImage(width,height);
//residual between input and denoised L channel
array2D<float> Ldetail(width,height,ARRAY2D_CLEAR_DATA);
//pixel weight
array2D<float> totwt(width,height,ARRAY2D_CLEAR_DATA);//weight for combining DCT blocks
//
//#ifdef _OPENMP
//#pragma omp parallel for
//#endif
//TODO: implement using AlignedBufferMP
//fill tile from image; convert RGB to "luma/chroma"
if (isRAW) {//image is raw; use channel differences for chroma channels
for (int i=tiletop/*, i1=0*/; i<tilebottom; i++/*, i1++*/) {
int i1 = i - tiletop;
for (int j=tileleft/*, j1=0*/; j<tileright; j++/*, j1++*/) {
int j1 = j - tileleft;
float X = gain*src->r(i,j);
float Y = gain*src->g(i,j);
float Z = gain*src->b(i,j);
X = X<65535.0f ? gamcurve[X] : (Color::gamma((double)X/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
Y = Y<65535.0f ? gamcurve[Y] : (Color::gamma((double)Y/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
Z = Z<65535.0f ? gamcurve[Z] : (Color::gamma((double)Z/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
labdn->L[i1][j1] = Y;
labdn->a[i1][j1] = (X-Y);
labdn->b[i1][j1] = (Y-Z);
// Ldetail[i1][j1] = 0;
Lin[i1][j1] = Y;
// totwt[i1][j1] = 0;
}
}
} else {//image is not raw; use Lab parametrization
for (int i=tiletop/*, i1=0*/; i<tilebottom; i++/*, i1++*/) {
int i1 = i - tiletop;
for (int j=tileleft/*, j1=0*/; j<tileright; j++/*, j1++*/) {
int j1 = j - tileleft;
//TODO: use embedded profile if present, instead of assuming sRGB
float rtmp = Color::igammatab_srgb[ src->r(i,j) ];
float gtmp = Color::igammatab_srgb[ src->g(i,j) ];
float btmp = Color::igammatab_srgb[ src->b(i,j) ];
//perhaps use LCH or YCrCb ???
float X = xyz_sRGB[0][0]*rtmp + xyz_sRGB[0][1]*gtmp + xyz_sRGB[0][2]*btmp;
float Y = xyz_sRGB[1][0]*rtmp + xyz_sRGB[1][1]*gtmp + xyz_sRGB[1][2]*btmp;
float Z = xyz_sRGB[2][0]*rtmp + xyz_sRGB[2][1]*gtmp + xyz_sRGB[2][2]*btmp;
X = X<65535.0f ? gamcurve[X] : (Color::gamma((double)X/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
Y = Y<65535.0f ? gamcurve[Y] : (Color::gamma((double)Y/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
Z = Z<65535.0f ? gamcurve[Z] : (Color::gamma((double)Z/65535.0, gam, gamthresh, gamslope, 1.0, 0.0)*32768.0f);
labdn->L[i1][j1] = Y;
labdn->a[i1][j1] = (X-Y);
labdn->b[i1][j1] = (Y-Z);
// Ldetail[i1][j1] = 0;
Lin[i1][j1] = Y;
// totwt[i1][j1] = 0;
}
}
}
//initial impulse denoise
if (dnparams.luma>0.01) {
impulse_nr (labdn, MIN(50.0f,dnparams.luma)/20.0f);
}
int datalen = labdn->W * labdn->H;
//now perform basic wavelet denoise
//last two arguments of wavelet decomposition are max number of wavelet decomposition levels;
//and whether to subsample the image after wavelet filtering. Subsampling is coded as
//binary 1 or 0 for each level, eg subsampling = 0 means no subsampling, 1 means subsample
//the first level only, 7 means subsample the first three levels, etc.
float noisevarL = SQR((dnparams.luma/125.0f)*(1+ dnparams.luma/25.0f));
float noisevarab = SQR(dnparams.chroma/10.0f);
{ // enclosing this code in a block frees about 120 MB before allocating 20 MB after this block (measured with D700 NEF)
wavelet_decomposition* Ldecomp;
wavelet_decomposition* adecomp;
wavelet_decomposition* bdecomp;
Ldecomp = new wavelet_decomposition (labdn->data, labdn->W, labdn->H, 5/*maxlevels*/, 0/*subsampling*/ );
adecomp = new wavelet_decomposition (labdn->data+datalen, labdn->W, labdn->H, 5, 1 );
bdecomp = new wavelet_decomposition (labdn->data+2*datalen, labdn->W, labdn->H, 5, 1 );
//WaveletDenoiseAll_BiShrink(Ldecomp, adecomp, bdecomp, noisevarL, noisevarab);
WaveletDenoiseAll(*Ldecomp, *adecomp, *bdecomp, noisevarL, noisevarab);
Ldecomp->reconstruct(labdn->data);
delete Ldecomp;
adecomp->reconstruct(labdn->data+datalen);
delete adecomp;
bdecomp->reconstruct(labdn->data+2*datalen);
delete bdecomp;
}
//TODO: at this point wavelet coefficients storage can be freed
//Issue 1680: Done now
//second impulse denoise
if (dnparams.luma>0.01) {
impulse_nr (labdn, MIN(50.0f,dnparams.luma)/20.0f);
}
//PF_correct_RT(dst, dst, defringe.radius, defringe.threshold);
//wavelet denoised L channel
array2D<float> Lwavdn(width,height);
float * Lwavdnptr = Lwavdn;
memcpy (Lwavdnptr, labdn->data, width*height*sizeof(float));
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// now do detail recovery using block DCT to detect
// patterns missed by wavelet denoise
// blocks are not the same thing as tiles!
// calculation for detail recovery blocks
const int numblox_W = ceil(((float)(width))/(offset))+2*blkrad;
const int numblox_H = ceil(((float)(height))/(offset))+2*blkrad;
//const int nrtiles = numblox_W*numblox_H;
// end of tiling calc
{
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// Main detail recovery algorithm: Block loop
//OpenMP here
//adding omp here leads to artifacts
AlignedBufferMP<float> buffer(width + TS + 2*blkrad*offset);
for (int vblk=0; vblk<numblox_H; vblk++) {
//printf("vblock=%d",vblk);
int vblkmod = vblk%8;
int top = (vblk-blkrad)*offset;
AlignedBuffer<float>* pBuf = buffer.acquire();
// float * buffer = new float [width + TS + 2*blkrad*offset];
float * datarow = (float*)pBuf->data +blkrad*offset;
//#ifdef _OPENMP
//#pragma omp parallel for
//#endif
//TODO: implement using AlignedBufferMP
// #pragma omp parallel for
for (int i=0/*, row=top*/; i<TS; i++/*, row++*/) {
int row = top + i;
int rr = row;
if (row<0) {
rr = MIN(-row,height-1);
} else if (row>=height) {
rr = MAX(0,2*height-2-row);
}
for (int j=0; j<labdn->W; j++) {
datarow[j] = (Lin[rr][j]-Lwavdn[rr][j]);
}
for (int j=-blkrad*offset; j<0; j++) {
datarow[j] = datarow[MIN(-j,width-1)];
}
for (int j=width; j<width+TS+blkrad*offset; j++) {
datarow[j] = datarow[MAX(0,2*width-2-j)];
}//now we have a padded data row
//now fill this row of the blocks with Lab high pass data
//OMP here does not add speed, better handled on the outside loop
for (int hblk=0; hblk<numblox_W; hblk++) {
int left = (hblk-blkrad)*offset;
int indx = (hblk)*TS;//index of block in malloc
for (int j=0; j<TS; j++) {
Lblox[(indx + i)*TS+j] = tilemask_in[i][j]*datarow[left+j];// luma data
if (top+i>=0 && top+i<height && left+j>=0 && left+j<width) {
totwt[top+i][left+j] += tilemask_in[i][j]*tilemask_out[i][j];
}
}
}
}//end of filling block row
buffer.release(pBuf);
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//fftwf_print_plan (plan_forward_blox);
if(numblox_W == max_numblox_W)
fftwf_execute_r2r(plan_forward_blox[0],Lblox,fLblox); // DCT an entire row of tiles
else
fftwf_execute_r2r(plan_forward_blox[1],Lblox,fLblox); // DCT an entire row of tiles
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// now process the vblk row of blocks for noise reduction
for (int hblk=0; hblk<numblox_W; hblk++) {
RGBtile_denoise (fLblox, vblk, hblk, numblox_H, numblox_W, noisevar_Ldetail );
}//end of horizontal block loop
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//now perform inverse FT of an entire row of blocks
if(numblox_W == max_numblox_W)
fftwf_execute_r2r(plan_backward_blox[0],fLblox,Lblox); //for DCT
else
fftwf_execute_r2r(plan_backward_blox[1],fLblox,Lblox); //for DCT
int topproc = (vblk-blkrad)*offset;
//add row of blocks to output image tile
RGBoutput_tile_row (Lblox, Ldetail, tilemask_out, height, width, topproc );
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
}//end of vertical block loop
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for (int i=0; i<height; i++) {
for (int j=0; j<width; j++) {
//may want to include masking threshold for large hipass data to preserve edges/detail
float hpdn = Ldetail[i][j]/totwt[i][j];//note that labdn initially stores the denoised hipass data
labdn->L[i][j] = Lwavdn[i][j] + hpdn;
}
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// transform denoised "Lab" to output RGB
//calculate mask for feathering output tile overlaps
float * Vmask = new float [height+1];
float * Hmask = new float [width+1];
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-i] = mask;
if (tileleft>0) Hmask[i] = mask;
if (tileright<imwidth) Hmask[width-i] = mask;
}
//convert back to RGB and write to destination array
if (isRAW) {
#ifdef _OPENMP
//#pragma omp parallel for
#endif
for (int i=tiletop; i<tilebottom; i++){
int i1 = i-tiletop;
float X,Y,Z;
for (int j=tileleft; j<tileright; j++) {
int j1=j-tileleft;
Y = labdn->L[i1][j1];
X = (labdn->a[i1][j1]) + Y;
Z = Y - (labdn->b[i1][j1]);
X = X<32768.0f ? igamcurve[X] : (Color::gamma((float)X/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
Y = Y<32768.0f ? igamcurve[Y] : (Color::gamma((float)Y/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
Z = Z<32768.0f ? igamcurve[Z] : (Color::gamma((float)Z/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
float factor = Vmask[i1]*Hmask[j1]/gain;
dsttmp->r(i,j) += factor*X;
dsttmp->g(i,j) += factor*Y;
dsttmp->b(i,j) += factor*Z;
}
}
} else {
#ifdef _OPENMP
//#pragma omp parallel for
#endif
for (int i=tiletop; i<tilebottom; i++){
int i1 = i-tiletop;
float X,Y,Z;
for (int j=tileleft; j<tileright; j++) {
int j1=j-tileleft;
Y = labdn->L[i1][j1];
X = (labdn->a[i1][j1]) + Y;
Z = Y - (labdn->b[i1][j1]);
X = X<32768.0f ? igamcurve[X] : (Color::gamma((float)X/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
Y = Y<32768.0f ? igamcurve[Y] : (Color::gamma((float)Y/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
Z = Z<32768.0f ? igamcurve[Z] : (Color::gamma((float)Z/32768.0f, igam, igamthresh, igamslope, 1.0, 0.0) * 65535.0f);
float factor = Vmask[i1]*Hmask[j1];
float rtmp = sRGB_xyz[0][0]*X + sRGB_xyz[0][1]*Y + sRGB_xyz[0][2]*Z;
float gtmp = sRGB_xyz[1][0]*X + sRGB_xyz[1][1]*Y + sRGB_xyz[1][2]*Z;
float btmp = sRGB_xyz[2][0]*X + sRGB_xyz[2][1]*Y + sRGB_xyz[2][2]*Z;
dsttmp->r(i,j) += factor*rtmp;
dsttmp->g(i,j) += factor*gtmp;
dsttmp->b(i,j) += factor*btmp;
}
}
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
delete labdn;
delete[] Vmask;
delete[] Hmask;
}//end of tile row
}//end of tile loop
#ifdef _OPENMP
#pragma omp critical
#endif
{
fftwf_free ( Lblox);
fftwf_free ( fLblox);
}
}
//copy denoised image to output
memcpy (dst->data, dsttmp->data, 3*dst->width*dst->height*sizeof(float));
if (!isRAW) {//restore original image gamma
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i=0; i<3*dst->width*dst->height; i++) {
dst->data[i] = Color::gammatab_srgb[ dst->data[i] ];
}
}
delete dsttmp;
// destroy the plans
fftwf_destroy_plan( plan_forward_blox[0] );
fftwf_destroy_plan( plan_backward_blox[0] );
fftwf_destroy_plan( plan_forward_blox[1] );
fftwf_destroy_plan( plan_backward_blox[1] );
fftwf_cleanup();
}//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
#pragma omp parallel for
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
int imin = MAX(0,-top);
int bottom = MIN( top+TS,height);
int imax = bottom - top;
#ifdef _OPENMP
#pragma omp parallel for
#endif
//add row of tiles to output image
for (int hblk=0; hblk < numblox_W; hblk++) {
int left = (hblk-blkrad)*offset;
int right = MIN(left+TS, width);
int jmin = MAX(0,-left);
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];
//OpenMP here
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);
AlignedBufferMP<double>* buffer = new AlignedBufferMP<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));
//OpenMP here
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);
//OpenMP here
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
//OpenMP here
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::WaveletDenoiseAll(wavelet_decomposition &WaveletCoeffs_L, wavelet_decomposition &WaveletCoeffs_a,
wavelet_decomposition &WaveletCoeffs_b, float noisevar_L, float noisevar_ab )
{
int maxlvl = WaveletCoeffs_L.maxlevel();
// printf("maxlevel = %d\n",maxlvl);
//omp_set_nested(true);
#ifdef _OPENMP
#pragma omp parallel for
#endif
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);
// printf("Hab : %d\n", Hlvl_ab);
// printf("Wab : %d\n", Wlvl_ab);
ShrinkAll(WavCoeffs_L, WavCoeffs_a, WavCoeffs_b, lvl, Wlvl_L, Hlvl_L, Wlvl_ab, Hlvl_ab,
skip_L, skip_ab, noisevar_L, noisevar_ab);
}
//omp_set_nested(false);
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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];
float * sfavea = new float[W_L*H_L];
float * sfaveb = 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));
//printf(" dir=%d mad_L=%f mad_a=%f mad_b=%f \n",dir,sqrt(madL),sqrt(mada),sqrt(madb));
float mad_L = madL*noisevar_L*5/(level+1);
float mad_a = mada*noisevar_ab;
float mad_b = madb*noisevar_ab;
if (noisevar_ab>0.01) {
//OpenMP here
#ifdef _OPENMP
#pragma omp parallel for
#endif
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;
sfavea[coeffloc_ab] = (1-exp(-(mag_a/mad_a)-(mag_L/(9*madL))));
sfaveb[coeffloc_ab] = (1-exp(-(mag_b/mad_b)-(mag_L/(9*madL))));
// 'firm' threshold of chroma coefficients
//WavCoeffs_a[dir][coeffloc_ab] *= (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] *= (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)));
}
}//now chrominance coefficients are denoised
boxblur(sfavea, sfavea, level+2, level+2, W_ab, H_ab);//increase smoothness by locally averaging shrinkage
boxblur(sfaveb, sfaveb, level+2, level+2, W_ab, H_ab);//increase smoothness by locally averaging shrinkage
#ifdef _OPENMP
#pragma omp parallel for
#endif
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 sfa = (1-exp(-(mag_a/mad_a)-(mag_L/(9*madL))));
float sfb = (1-exp(-(mag_b/mad_b)-(mag_L/(9*madL))));
//use smoothed shrinkage unless local shrinkage is much less
WavCoeffs_a[dir][coeffloc_ab] *= (SQR(sfavea[coeffloc_ab])+SQR(sfa))/(sfavea[coeffloc_ab]+sfa+eps);
WavCoeffs_b[dir][coeffloc_ab] *= (SQR(sfaveb[coeffloc_ab])+SQR(sfb))/(sfaveb[coeffloc_ab]+sfb+eps);
}//now chrominance coefficients are denoised
}
if (noisevar_L>0.01) {
//OpenMP here
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i=0; i<W_L*H_L; i++) {
float mag = SQR(WavCoeffs_L[dir][i]);
float shrinkfactor = mag/(mag+mad_L*exp(-mag/(9*mad_L))+eps);
//WavCoeffs_L[dir][i] *= shrinkfactor;
sfave[i] = shrinkfactor;
}
//OpenMP here
boxblur(sfave, sfave, level+2, level+2, W_L, H_L);//increase smoothness by locally averaging shrinkage
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int i=0; i<W_L*H_L; i++) {
float mag = SQR(WavCoeffs_L[dir][i]);
float sf = mag/(mag+mad_L*exp(-mag/(9*mad_L))+eps);
//use smoothed shrinkage unless local shrinkage is much less
WavCoeffs_L[dir][i] *= (SQR(sfave[i])+SQR(sf))/(sfave[i]+sf+eps);
}//now luminance coefficients are denoised
}
}
delete[] sfave;
delete[] sfavea;
delete[] sfaveb;
}
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
}
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