OMP optimizations for NR

rtdata/profiles/Default-ISO-Medium.pp3

@@ -80,7 +80,7 @@ Temperature=5745
 Green=1.0
 
 [Impulse Denoising]
-Enabled=true
+Enabled=false
 Threshold=50
 
 [Defringing]

rtengine/EdgePreserveLab.cc

@@ -2,6 +2,10 @@
 #include "boxblur.h"
 #include <cstdlib>
 
+#ifdef _OPENMP
+#include <omp.h>
+#endif
+
 //#define MAX(a,b) ((a)<(b)?(b):(a))
 //#define MIN(a,b) ((a)>(b)?(b):(a))
 
@@ -62,9 +66,12 @@ float *EdgePreserveLab::CreateBlur(float *Source, float LScale, float abScale, f
 	float * var = new float[w*h];
 	rtengine::boxvar(g, var, 1, 1, w, h);
 
-	for(y = 0; y != h1; y++){
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
+	for(y = 0; y < h1; y++){
 		float *rg = &g[w*y];
-		for(x = 0; x != w1; x++){
+		for(x = 0; x < w1; x++){
 			//Estimate the central difference gradient in the center of a four pixel square. (gx, gy) is actually 2*gradient.
 			/*float gx = (fabs((rg[x + 1] - rg[x]) + (rg[x + w + 1] - rg[x + w])));
 			float gy = (fabs((rg[x + w] - rg[x]) + (rg[x + w + 1] - rg[x + 1])));
@@ -103,6 +110,8 @@ float *EdgePreserveLab::CreateBlur(float *Source, float LScale, float abScale, f
 	memset(a_w1, 0, A->DiagonalLength(w - 1)*sizeof(float));
 	memset(a_w, 0, A->DiagonalLength(w)*sizeof(float));
 	memset(a_w_1, 0, A->DiagonalLength(w + 1)*sizeof(float));
+
+//TODO: OMP here?
 	for(i = y = 0; y != h; y++){
 		for(x = 0; x != w; x++, i++){
 			float ac;

rtengine/FTblockDN.cc

@@ -98,6 +98,9 @@ namespace rtengine {
 		const short int imheight=src->height, imwidth=src->width;
 		
 		if (dnparams.luma==0 && dnparams.chroma==0) {//nothing to do; copy src to dst
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 			for (int i=0; i<imheight; i++) {
 				for (int j=0; j<imwidth; j++) {
 					dst->r[i][j] = src->r[i][j];
@@ -145,6 +148,9 @@ namespace rtengine {
 		
 		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);
@@ -164,6 +170,9 @@ namespace rtengine {
 		
 		//output buffer
 		Imagefloat * dsttmp = new Imagefloat(imwidth,imheight);
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int n=0; n<3*imwidth*imheight; n++) {
 			dsttmp->data[n] = 0;
 		}
@@ -196,7 +205,6 @@ namespace rtengine {
 		//now we have tile dimensions, overlaps
 		//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-		
 		for (int tiletop=0; tiletop<imheight; tiletop+=tileHskip) {
 			for (int tileleft=0; tileleft<imwidth; tileleft+=tileWskip) {
 				
@@ -214,6 +222,7 @@ namespace rtengine {
 				//pixel weight
 				array2D<float> totwt(width,height,ARRAY2D_CLEAR_DATA);//weight for combining DCT blocks
 
+// OMP candidate?
 				//fill tile from image; convert RGB to "luma/chroma"
 				for (int i=tiletop, i1=0; i<tilebottom; i++, i1++) 
 					for (int j=tileleft, j1=0; j<tileright; j++, j1++) {
@@ -340,6 +349,9 @@ namespace rtengine {
 						}//now we have a padded data row
 						
 						//now fill this row of the blocks with Lab high pass data
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif							
 						for (int hblk=0; hblk<numblox_W; hblk++) {
 							int left = (hblk-blkrad)*offset;
 							int indx = (hblk)*TS;//index of block in malloc
@@ -361,6 +373,9 @@ namespace rtengine {
 					
 					//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 					// now process the vblk row of blocks for noise reduction
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif	
 					for (int hblk=0; hblk<numblox_W; hblk++) {
 						
 						RGBtile_denoise (fLblox, vblk, hblk, numblox_H, numblox_W, noisevar_Ldetail );
@@ -395,7 +410,9 @@ namespace rtengine {
 				fftwf_cleanup();
 				
 				//%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-				
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif					
 				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
@@ -427,6 +444,7 @@ namespace rtengine {
 					if (tileright<imwidth) Hmask[width-1-i] = mask;
 				}
 
+//TODO: OMP candidate?
 				//convert back to RGB and write to destination array
 				for (int i=tiletop, i1=0; i<tilebottom; i++, i1++) {
 					float X,Y,Z;
@@ -460,7 +478,7 @@ namespace rtengine {
 			}//end of tile row
 		}//end of tile loop
 		
-	
+//TODO: is memcpy multithreaded - should this be replaced with the OMP-ed for loop?	
 	//copy denoised image to output
 	memcpy (dst->data, dsttmp->data, 3*imwidth*imheight*sizeof(float));
 	
@@ -483,6 +501,9 @@ namespace rtengine {
 		
 		boxabsblur(fLblox+blkstart, nbrwt, 3, 3, TS, TS);//blur neighbor weights for more robust estimation	//for DCT
 
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif			
 		for (int n=0; n<TS*TS; n++) {		//for DCT
 			fLblox[blkstart+n] *= (1-expf(-SQR(nbrwt[n])/noisevar_Ldetail));
 		}//output neighbor averaged result
@@ -503,6 +524,9 @@ namespace rtengine {
 		const int numblox_W = ceil(((float)(width))/(offset));
 		const float DCTnorm = 1.0f/(4*TS*TS); //for DCT
 
+#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;
@@ -544,6 +568,9 @@ namespace rtengine {
 		for (int i=0; i<65536; i++) histo[i]=0;
 		
 		//calculate histogram of absolute values of HH wavelet coeffs
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif		
 		for (int i=0; i<datalen; i++) {
 			histo[MAX(0,MIN(65535,abs((int)DataList[i])))]++;
 		}
@@ -744,6 +771,9 @@ namespace rtengine {
 	{
 		int maxlvl = WaveletCoeffs_L.maxlevel();
 
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int lvl=0; lvl<maxlvl; lvl++) {
 			
 			int Wlvl_L = WaveletCoeffs_L.level_W(lvl);
@@ -780,7 +810,9 @@ namespace rtengine {
 		int max;
 		
 		printf("\n level=%d  \n",level);
-		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif			
 		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));
@@ -795,6 +827,10 @@ namespace rtengine {
 			
 			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++) {
 						
@@ -818,6 +854,10 @@ namespace rtengine {
 				
 				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
+//MK
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 				for (int i=0; i<H_ab; i++) 
 					for (int j=0; j<W_ab; j++) {
 						
@@ -840,6 +880,9 @@ namespace rtengine {
 			
 			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]);
@@ -850,6 +893,9 @@ namespace rtengine {
 				}
 //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++) {
 					
 					

rtengine/boxblur.h

@@ -48,6 +48,9 @@ template<class T, class A> void boxblur (T** src, A** dst, int radx, int rady, i
 	float* temp = buffer->data;
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				temp[row*H+col] = (float)src[row][col];
@@ -55,6 +58,9 @@ template<class T, class A> void boxblur (T** src, A** dst, int radx, int rady, i
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = (float)src[row][0]/len;
@@ -76,6 +82,9 @@ template<class T, class A> void boxblur (T** src, A** dst, int radx, int rady, i
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row][col] = temp[row*W+col];
@@ -83,6 +92,9 @@ template<class T, class A> void boxblur (T** src, A** dst, int radx, int rady, i
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0][col] = temp[0*W+col]/len;
@@ -127,6 +139,9 @@ template<class T, class A> void boxblur (T* src, A* dst, int radx, int rady, int
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = (float)src[row*W+0]/len;
@@ -148,6 +163,9 @@ template<class T, class A> void boxblur (T* src, A* dst, int radx, int rady, int
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row*W+col] = temp[row*W+col];
@@ -155,6 +173,9 @@ template<class T, class A> void boxblur (T* src, A* dst, int radx, int rady, int
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0*W+col] = temp[0*W+col]/len;
@@ -282,6 +303,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	float* tempave = buffer2->data;
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif	
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				temp[row*H+col] = src[row*W+col];
@@ -289,6 +313,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = (float)src[row*W+0]/len;
@@ -311,12 +338,18 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	
 	if (rady==0) {
 		for (int row=0; row<H; row++) 
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 			for (int col=0; col<H; col++) {
 				tempave[row*W+col] = temp[row*W+col];
 			}
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			tempave[0*W+col] = temp[0*W+col]/len;
@@ -342,6 +375,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				temp[row*H+col] = fabs(src[row*W+col]-tempave[row*W+col]);
@@ -349,6 +385,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	} else {
 		//horizontal blur
 //OpenMP here
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif		
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = fabs(src[row*W+0]-tempave[row*W+0])/len;
@@ -371,6 +410,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row*W+col] = temp[row*W+col];
@@ -378,6 +420,9 @@ template<typename T> void boxdev (T* src, T* dst, int radx, int rady, int W, int
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0*W+col] = temp[0*W+col]/len;
@@ -416,6 +461,9 @@ template<class T, class A> void boxsqblur (T* src, A* dst, int radx, int rady, i
 	float* temp = buffer->data;
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				temp[row*H+col] = SQR(src[row*W+col]);
@@ -423,6 +471,9 @@ template<class T, class A> void boxsqblur (T* src, A* dst, int radx, int rady, i
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = SQR((float)src[row*W+0])/len;
@@ -444,6 +495,9 @@ template<class T, class A> void boxsqblur (T* src, A* dst, int radx, int rady, i
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row*W+col] = temp[row*W+col];
@@ -451,6 +505,9 @@ template<class T, class A> void boxsqblur (T* src, A* dst, int radx, int rady, i
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0*W+col] = temp[0*W+col]/len;
@@ -488,6 +545,9 @@ template<class T, class A> void boxcorrelate (T* src, A* dst, int dx, int dy, in
 	float* temp = buffer->data;
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) {
 			int rr = min(H-1,max(0,row+dy));
 			for (int col=0; col<H; col++) {
@@ -498,6 +558,9 @@ template<class T, class A> void boxcorrelate (T* src, A* dst, int dx, int dy, in
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			int rr = min(H-1,max(0,row+dy));
@@ -527,6 +590,9 @@ template<class T, class A> void boxcorrelate (T* src, A* dst, int dx, int dy, in
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row*W+col] = temp[row*W+col];
@@ -534,6 +600,9 @@ template<class T, class A> void boxcorrelate (T* src, A* dst, int dx, int dy, in
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0*W+col] = temp[0*W+col]/len;
@@ -572,6 +641,9 @@ template<class T, class A> void boxabsblur (T* src, A* dst, int radx, int rady,
 	float* temp = buffer->data;
 	
 	if (radx==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				temp[row*H+col] = fabs(src[row*W+col]);
@@ -579,6 +651,9 @@ template<class T, class A> void boxabsblur (T* src, A* dst, int radx, int rady,
 	} else {
 		//horizontal blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row = 0; row < H; row++) {
 			int len = radx + 1;
 			temp[row*W+0] = fabs((float)src[row*W+0])/len;
@@ -600,6 +675,9 @@ template<class T, class A> void boxabsblur (T* src, A* dst, int radx, int rady,
 	}
 	
 	if (rady==0) {
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int row=0; row<H; row++) 
 			for (int col=0; col<H; col++) {
 				dst[row*W+col] = temp[row*W+col];
@@ -607,6 +685,9 @@ template<class T, class A> void boxabsblur (T* src, A* dst, int radx, int rady,
 	} else {
 		//vertical blur
 //OpenMP here		
+#ifdef _OPENMP
+#pragma omp parallel for
+#endif
 		for (int col = 0; col < W; col++) {
 			int len = rady + 1;
 			dst[0*W+col] = temp[0*W+col]/len;