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CFA line denoise improvements on behalf of Emil and Jacques; see issue #408

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This commit is contained in:
Oliver Duis 2010-12-21 22:54:10 +01:00
parent 84b7e9b6ea
commit f90f4fb7d5
1 changed files with 131 additions and 60 deletions
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191
rtengine/cfa_linedn_RT.cc
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@ -27,8 +27,8 @@
#define CLASS #define CLASS
/*
/*#include <ctype.h> #include <ctype.h>
#include <errno.h> #include <errno.h>
#include <fcntl.h> #include <fcntl.h>
#include <float.h> #include <float.h>
@ -59,22 +59,24 @@ void RawImageSource::CLASS cfa_linedn(float noise)
{ {
// local variables // local variables
int height=H, width=W; int height=H, width=W;
int top, left, row, col;
int rr, cc, indx, i, j;
int ex, ey;
int verbose=1; int verbose=1;
const float clip_pt = 0.8*initialGain* 65535.0; const float clip_pt = 0.8*initialGain* 65535.0;
float eps=1e-5; //tolerance to avoid dividing by zero float eps=1e-5; //tolerance to avoid dividing by zero
float gauss[5] = {0.20416368871516755, 0.18017382291138087, 0.1238315368057753, 0.0662822452863612, 0.02763055063889883}; const float gauss[5] = {0.20416368871516755, 0.18017382291138087, 0.1238315368057753, 0.0662822452863612, 0.02763055063889883};
float rolloff[8] = {0, 0.135335, 0.249352, 0.411112, 0.606531, 0.800737, 0.945959, 1}; //gaussian with sigma=3 const float rolloff[8] = {0, 0.135335, 0.249352, 0.411112, 0.606531, 0.800737, 0.945959, 1}; //gaussian with sigma=3
float window[8] = {0, .25, .75, 1, 1, .75, .25, 0}; //sine squared const float window[8] = {0, .25, .75, 1, 1, .75, .25, 0}; //sine squared
float noisevar, linehvar, linevvar, coeffsq;
float aarr[4][8][8], *bbrr[4][8], **dctblock[4];
for (int j=0; j<4; j++) {
for (int i = 0; i < 8; i++)
bbrr[j][i] = aarr[j][i];
dctblock[j] = bbrr[j];
}
float aarr[8][8], *dctblock[8];
for (i = 0; i < 8; i++) dctblock[i] = aarr[i];
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@ -84,124 +86,193 @@ void RawImageSource::CLASS cfa_linedn(float noise)
} }
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
float noisevar=SQR(3*noise*65535); // _noise_ (as a fraction of saturation) is input to the algorithm
volatile double progress = 0.0;
#pragma omp parallel
{
noisevar=SQR(3*noise*65535); // _noise_ (as a fraction of saturation) is input to the algorithm
float *cfain= new float[TS*TS]; float *cfain= new float[TS*TS];
float *cfablur= new float[TS*TS]; float *cfablur= new float[TS*TS];
float *cfadiff= new float[TS*TS]; float *cfadiff= new float[TS*TS];
float *cfadn= new float[TS*TS]; float *cfadn= new float[TS*TS];
/*
char *buffer; // TS*TS*16
float (*cfain); // TS*TS*4
float (*cfablur); // TS*TS*4
float (*cfadiff); // TS*TS*4
float (*cfadn); // TS*TS*4
buffer = (char *) calloc((3*sizeof(float)+sizeof(int))*TS*TS,1);// 16
// merror(buffer,"cfa_linedn()");
// memset(buffer,0,16*TS*TS);
cfain = (float (*)) buffer; //pointers to rows of array
cfablur = (float (*)) (buffer + sizeof(float)*TS*TS); //4
cfadiff = (float (*)) (buffer + 2*sizeof(float)*TS*TS);//8
cfadn = (float (*)) (buffer + 3*sizeof(float)*TS*TS);//12
*/
// Main algorithm: Tile loop // Main algorithm: Tile loop
for (top=0; top < height-16; top += TS-32) #pragma omp for schedule(dynamic) nowait
for (left=0; left < width-16; left += TS-32) { for (int top=0; top < height-16; top += TS-32)
for (int left=0; left < width-16; left += TS-32) {
int bottom = MIN( top+TS,height); int bottom = MIN( top+TS,height);
int right = MIN(left+TS, width); int right = MIN(left+TS, width);
int numrows = bottom - top; int numrows = bottom - top;
int numcols = right - left; int numcols = right - left;
int indx1;
// load CFA data; data should be in linear gamma space, before white balance multipliers are applied // load CFA data; data should be in linear gamma space, before white balance multipliers are applied
for (rr=top; rr < top+numrows; rr++) for (int rr=top; rr < top+numrows; rr++)
for (cc=left, indx=(rr-top)*TS; cc < left+numcols; cc++, indx++) { for (int cc=left, indx=(rr-top)*TS; cc < left+numcols; cc++, indx++) {
cfain[indx] = rawData[rr][cc]; cfain[indx] = rawData[rr][cc];
} }
//pad the block to a multiple of 16 on both sides //pad the block to a multiple of 16 on both sides
if (numcols < TS) { if (numcols < TS) {
indx=numcols % 16; indx1=numcols % 16;
for (i=0; i<(16-indx); i++) for (int i=0; i<(16-indx1); i++)
for (rr=0; rr<numrows; rr++) for (int rr=0; rr<numrows; rr++)
cfain[(rr)*TS+numcols+i+1]=cfain[(rr)*TS+numcols-i]; cfain[(rr)*TS+numcols+i+1]=cfain[(rr)*TS+numcols-i];
numcols += 16-indx; numcols += 16-indx1;
} }
if (numrows < TS) { if (numrows < TS) {
indx=numrows % 16; indx1=numrows % 16;
for (i=0; i<(16-indx); i++) for (int i=0; i<(16-indx1); i++)
for (cc=0; cc<numcols; cc++) for (int cc=0; cc<numcols; cc++)
cfain[(numrows+i+1)*TS+cc]=cfain[(numrows-i)*TS+cc]; cfain[(numrows+i+1)*TS+cc]=cfain[(numrows-i)*TS+cc];
numrows += 16-indx; numrows += 16-indx1;
} }
//The cleaning algorithm starts here //The cleaning algorithm starts here
//gaussian blur of CFA data //gaussian blur of CFA data
for (rr=8; rr < numrows-8; rr++) for (int rr=8; rr < numrows-8; rr++)
for (indx=rr*TS; indx < rr*TS+numcols; indx++) { for (int indx=rr*TS; indx < rr*TS+numcols; indx++) {
cfablur[indx]=gauss[0]*cfain[indx]; cfablur[indx]=gauss[0]*cfain[indx];
for (i=1; i<5; i++) { for (int i=1; i<5; i++) {
cfablur[indx] += gauss[i]*(cfain[indx-(2*i)*TS]+cfain[indx+(2*i)*TS]); cfablur[indx] += gauss[i]*(cfain[indx-(2*i)*TS]+cfain[indx+(2*i)*TS]);
} }
} }
for (rr=8; rr < numrows-8; rr++) for (int rr=8; rr < numrows-8; rr++)
for (indx=rr*TS+8; indx < rr*TS+numcols-8; indx++) { for (int indx=rr*TS+8; indx < rr*TS+numcols-8; indx++) {
cfadn[indx] = gauss[0]*cfablur[indx]; cfadn[indx] = gauss[0]*cfablur[indx];
for (i=1; i<5; i++) { for (int i=1; i<5; i++) {
cfadn[indx] += gauss[i]*(cfablur[indx-2*i]+cfablur[indx+2*i]); cfadn[indx] += gauss[i]*(cfablur[indx-2*i]+cfablur[indx+2*i]);
} }
cfadiff[indx]=cfain[indx]-cfadn[indx]; // hipass cfa data cfadiff[indx]=cfain[indx]-cfadn[indx]; // hipass cfa data
} }
//begin block DCT //begin block DCT
for (ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray float linehvar[4], linevvar[4], noisefactor[4][8][2], coeffsq;
for (ex=0; ex<2; ex++) #pragma omp critical
for (rr=8+ey; rr < numrows-22; rr+=8) // (rr,cc) shift by 8 to overlap blocks {
for (cc=8+ex; cc < numcols-22; cc+=8) { for (int rr=8; rr < numrows-22; rr+=8) // (rr,cc) shift by 8 to overlap blocks
for (int cc=8; cc < numcols-22; cc+=8) {
for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
for (int ex=0; ex<2; ex++) {
//grab an 8x8 block of a given RGGB channel //grab an 8x8 block of a given RGGB channel
for (i=0; i<8; i++) for (int i=0; i<8; i++)
for (j=0; j<8; j++) { for (int j=0; j<8; j++) {
dctblock[i][j]=cfadiff[(rr+2*i)*TS+cc+2*j]; dctblock[2*ey+ex][i][j]=cfadiff[(rr+2*i+ey)*TS+cc+2*j+ex];
} }
ddct8x8s(-1, dctblock); //forward DCT ddct8x8s(-1, dctblock[2*ey+ex]); //forward DCT
}
for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
for (int ex=0; ex<2; ex++) {
linehvar[2*ey+ex]=linevvar[2*ey+ex]=0;
for (int i=4; i<8; i++) {
linehvar[2*ey+ex] += SQR(dctblock[2*ey+ex][0][i]);
linevvar[2*ey+ex] += SQR(dctblock[2*ey+ex][i][0]);
linehvar=linevvar=0;
for (i=4; i<8; i++) {
linehvar += SQR(dctblock[0][i]);
linevvar += SQR(dctblock[i][0]);
} }
//Wiener filter for line denoising; roll off low frequencies //Wiener filter for line denoising; roll off low frequencies
if (noisevar>linehvar) { for (int i=1; i<8; i++) {
for (i=1; i<8; i++) { coeffsq = SQR(dctblock[2*ey+ex][i][0]);//vertical
coeffsq=SQR(dctblock[0][i]); noisefactor[2*ey+ex][i][0] = coeffsq/(coeffsq+rolloff[i]*noisevar+eps);
dctblock[0][i] *= coeffsq/(coeffsq+rolloff[i]*noisevar+eps); coeffsq = SQR(dctblock[2*ey+ex][0][i]);//horizontal
noisefactor[2*ey+ex][i][1] = coeffsq/(coeffsq+rolloff[i]*noisevar+eps);
// noisefactor labels are [RGGB subarray][row/col position][0=vert,1=hor]
} }
} }
if (noisevar>linevvar) { //horizontal lines
for (i=1; i<8; i++) { if (4*noisevar>(linehvar[0]+linehvar[1])) {//horizontal lines
coeffsq=SQR(dctblock[i][0]); for (int i=1; i<8; i++) {
dctblock[i][0] *= coeffsq/(coeffsq+rolloff[i]*noisevar+eps); dctblock[0][0][i] *= 0.5*(noisefactor[0][i][1]+noisefactor[1][i][1]);//or should we use MIN???
dctblock[1][0][i] *= 0.5*(noisefactor[0][i][1]+noisefactor[1][i][1]);//or should we use MIN???
}
}
if (4*noisevar>(linehvar[2]+linehvar[3])) {//horizontal lines
for (int i=1; i<8; i++) {
dctblock[2][0][i] *= 0.5*(noisefactor[2][i][1]+noisefactor[3][i][1]);//or should we use MIN???
dctblock[3][0][i] *= 0.5*(noisefactor[2][i][1]+noisefactor[3][i][1]);//or should we use MIN???
} }
} }
ddct8x8s(1, dctblock); //inverse DCT //vertical lines
if (4*noisevar>(linevvar[0]+linevvar[2])) {//vertical lines
for (int i=1; i<8; i++) {
dctblock[0][i][0] *= 0.5*(noisefactor[0][i][0]+noisefactor[2][i][0]);//or should we use MIN???
dctblock[2][i][0] *= 0.5*(noisefactor[0][i][0]+noisefactor[2][i][0]);//or should we use MIN???
}
}
if (4*noisevar>(linevvar[1]+linevvar[3])) {//vertical lines
for (int i=1; i<8; i++) {
dctblock[1][i][0] *= 0.5*(noisefactor[1][i][0]+noisefactor[3][i][0]);//or should we use MIN???
dctblock[3][i][0] *= 0.5*(noisefactor[1][i][0]+noisefactor[3][i][0]);//or should we use MIN???
}
}
for (int ey=0; ey<2; ey++) // (ex,ey) specify RGGB subarray
for (int ex=0; ex<2; ex++) {
ddct8x8s(1, dctblock[2*ey+ex]); //inverse DCT
//multiply by window fn and add to output (cfadn) //multiply by window fn and add to output (cfadn)
for (i=0; i<8; i++) for (int i=0; i<8; i++)
for (j=0; j<8; j++) { for (int j=0; j<8; j++) {
cfadn[(rr+2*i)*TS+cc+2*j] += window[i]*window[j]*dctblock[i][j]; cfadn[(rr+2*i+ey)*TS+cc+2*j+ex] += window[i]*window[j]*dctblock[2*ey+ex][i][j];
} }
} }
}
}
// %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% // %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
// copy smoothed results back to image matrix // copy smoothed results back to image matrix
for (rr=16; rr < numrows-16; rr++) { for (int rr=16; rr < numrows-16; rr++) {
row = rr + top; int row = rr + top;
for (col=16+left, indx=rr*TS+16; indx < rr*TS+numcols-16; indx++, col++) { for (int col=16+left, indx=rr*TS+16; indx < rr*TS+numcols-16; indx++, col++) {
if (rawData[row][col]<clip_pt && cfadn[indx]<clip_pt) if (rawData[row][col]<clip_pt && cfadn[indx]<clip_pt)
rawData[row][col] = CLIP((int)(cfadn[indx]+ 0.5)); rawData[row][col] = CLIP((int)(cfadn[indx]+ 0.5));
} }
} }
if(plistener) plistener->setProgress(fabs((float)top/height)); progress+=(double)((TS-32)*(TS-32))/(height*width);
if (progress>1.0)
{
progress=1.0;
}
if(plistener) plistener->setProgress(progress);
//if(plistener) plistener->setProgress(fabs((float)top/height));
} }
// clean up // clean up
delete [] cfain; delete [] cfain;
delete [] cfablur; delete [] cfablur;
delete [] cfadiff; delete [] cfadiff;
delete [] cfadn; delete [] cfadn;
//free(buffer);
}
} }
#undef TS #undef TS