Implemented variable fat zero, depending on per-tile number of averaging

src/TileProcessor.cuh

@@ -921,7 +921,7 @@ __device__ void resetCorrelation(
 
 __device__ void normalizeTileAmplitude(
 		float * clt_tile, //       [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
-		float fat_zero);  // fat zero is absolute, scale it outside
+		float fat_zero2);  // fat zero is absolute, scale it outside
 
 __device__ void imclt8threads(// for 8 threads
 		int     do_acc,     // 1 - add to previous value, 0 - overwrite
@@ -1076,7 +1076,7 @@ extern "C" __global__ void correlate2D_inner(
 		float             scale0,             // scale for R
 		float             scale1,             // scale for B
 		float             scale2,             // scale for G
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,           // here - absolute
 		size_t            num_corr_tiles,     // number of correlation tiles to process
 		int             * gpu_corr_indices,   // packed tile+pair
 		const size_t      corr_stride,        // in floats
@@ -1087,9 +1087,10 @@ extern "C" __global__ void corr2D_normalize_inner(
 		int               num_corr_tiles,     // number of correlation tiles to process
 		const size_t      corr_stride_td,     // (in floats) stride for the input TD correlations
 		float           * gpu_corrs_td,       // correlation tiles in transform domain
+		float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
 		const size_t      corr_stride,        // in floats
 		float           * gpu_corrs,          // correlation output data (either pixel domain or transform domain
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,          // here - absolute
 		int               corr_radius);        // radius of the output correlation (7 for 15x15)
 
 extern "C" __global__ void corr2D_combine_inner(
@@ -1151,7 +1152,7 @@ __device__ int get_textures_shared_size( // in bytes
  * @param scale0           scale red (or mono) component before mixing
  * @param scale1           scale blue (if colors = 3) component before mixing
  * @param scale2           scale green (if colors = 3) component before mixing
- * @param fat_zero         add this value squared to the sum of squared components before normalization\
+ * @param fat_zero2        add this value squared to the sum of squared components before normalization (squared)
  * @param gpu_ftasks           flattened tasks, 29 floats for quad EO, 101 floats for LWIR16
 // * @param gpu_tasks        array of per-tile tasks (now bits 4..9 - correlation pairs)
  * @param num_tiles        number of tiles int gpu_tasks array prepared for processing
@@ -1174,7 +1175,7 @@ extern "C" __global__ void correlate2D(
 		float             scale0,             // scale for R
 		float             scale1,             // scale for B
 		float             scale2,            // scale for G
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,           // here - absolute
 		float            * gpu_ftasks,         // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
 //		struct tp_task  * gpu_tasks,          // array of per-tile tasks (now bits 4..9 - correlation pairs)
 		int               num_tiles,          // number of tiles in task
@@ -1211,7 +1212,7 @@ extern "C" __global__ void correlate2D(
 				 scale0,             // float             scale0,             // scale for R
 				 scale1,             // float             scale1,             // scale for B
 				 scale2,             // float             scale2,             // scale for G
-				 fat_zero,           // float             fat_zero,           // here - absolute
+				 fat_zero2,          // float             fat_zero2,           // here - absolute
 				 *pnum_corr_tiles,   // size_t            num_corr_tiles,     // number of correlation tiles to process
 				 gpu_corr_indices,   //  int             * gpu_corr_indices,  // packed tile+pair
 				 corr_stride,        // const size_t      corr_stride,        // in floats
@@ -1231,7 +1232,7 @@ extern "C" __global__ void correlate2D(
  * @param scale0           scale red (or mono) component before mixing
  * @param scale1           scale blue (if colors = 3) component before mixing
  * @param scale2           scale green (if colors = 3) component before mixing
- * @param fat_zero         add this value squared to the sum of squared components before normalization
+ * @param fat_zero2        add this value squared to the sum of squared components before normalization
  * @param num_corr_tiles   number of correlation tiles to process
  * @param gpu_corr_indices packed array (each element, integer contains tile+pair) of correlation tasks
  * @param corr_stride,     stride (in floats) for correlation outputs.
@@ -1245,7 +1246,7 @@ extern "C" __global__ void correlate2D_inner(
 		float             scale0,             // scale for R
 		float             scale1,             // scale for B
 		float             scale2,             // scale for G
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,          // here - absolute
 		size_t            num_corr_tiles,     // number of correlation tiles to process
 		int             * gpu_corr_indices,   // packed tile+pair
 		const size_t      corr_stride,        // in floats
@@ -1384,13 +1385,13 @@ extern "C" __global__ void correlate2D_inner(
     if (corr_radius > 0) {
     	normalizeTileAmplitude(
     			clt_corr,   // float * clt_tile, //       [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
-				fat_zero); // float fat_zero ) // fat zero is absolute, scale it outside
+				fat_zero2); // float fat_zero2 ) // fat zero is absolute, scale it outside
     	// Low Pass Filter from constant area (is it possible to replace?)
 
 #ifdef DBG_TILE
 #ifdef DEBUG6
     	if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
-    		printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero=%f\n",fat_zero);
+    		printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero2=%f\n",fat_zero2);
     		debug_print_clt1(clt_corr, -1,  0xf);
     	}
     	__syncthreads();// __syncwarp();
@@ -1695,18 +1696,20 @@ extern "C" __global__ void corr2D_combine_inner(
  * @param num_tiles        number of correlation tiles to process
  * @param corr_stride_td,  stride (in floats) for correlation input (transform domain).
  * @param gpu_corrs_td     correlation data in transform domain
+ * @param corr_weights      null or per-tile weight (fat_zero2 will be divided by it)
  * @param corr_stride,     stride (in floats) for correlation pixel-domain outputs.
  * @param gpu_corrs        allocated array for the correlation output data (each element stride, payload: (2*corr_radius+1)^2
- * @param fat_zero         add this value squared to the sum of squared components before normalization
+ * @param fat_zero2        add this value squared to the sum of squared components before normalization (squared)
  * @param corr_radius,     radius of the output correlation (maximal 7 for 15x15)
  */
 extern "C" __global__ void corr2D_normalize(
 		int               num_corr_tiles,     // number of correlation tiles to process
 		const size_t      corr_stride_td,     // in floats
 		float           * gpu_corrs_td,       // correlation tiles in transform domain
+		float           * corr_weights,       // null or per correlation tile weight (fat_zero2 will be divided by it)
 		const size_t      corr_stride,        // in floats
 		float           * gpu_corrs,          // correlation output data (either pixel domain or transform domain
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,          // here - absolute, squared
 		int               corr_radius)        // radius of the output correlation (7 for 15x15)
 {
 	 if (threadIdx.x == 0) { // only 1 thread, 1 block
@@ -1716,9 +1719,10 @@ extern "C" __global__ void corr2D_normalize(
 	        		num_corr_tiles,      // int               num_corr_tiles,     // number of correlation tiles to process
 					corr_stride_td,      // const size_t      corr_stride,        // in floats
 					gpu_corrs_td,        // float           * gpu_corrs_td,       // correlation tiles in transform domain
+					corr_weights,        // float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
 					corr_stride,         // const size_t      corr_stride,        // in floats
 					gpu_corrs,           // float           * gpu_corrs,          // correlation output data (either pixel domain or transform domain
-					fat_zero,            // float             fat_zero,           // here - absolute
+					fat_zero2,            // float            fat_zero2,           // here - absolute
 					corr_radius);        // int               corr_radius,        // radius of the output correlation (7 for 15x15)
 	 }
 }
@@ -1730,9 +1734,10 @@ extern "C" __global__ void corr2D_normalize(
  * @param num_tiles        number of correlation tiles to process
  * @param corr_stride_td,  stride (in floats) for correlation input (transform domain).
  * @param gpu_corrs_td     correlation data in transform domain
+ * @param corr_weights      null or per-tile weight (fat_zero2 will be divided by it)
  * @param corr_stride,     stride (in floats) for correlation pixel-domain outputs.
  * @param gpu_corrs        allocated array for the correlation output data (each element stride, payload: (2*corr_radius+1)^2
- * @param fat_zero         add this value squared to the sum of squared components before normalization
+ * @param fat_zero2        add this value squared to the sum of squared components before normalization
  * @param corr_radius,     radius of the output correlation (maximal 7 for 15x15)
  */
 
@@ -1740,9 +1745,10 @@ extern "C" __global__ void corr2D_normalize_inner(
 		int               num_corr_tiles,     // number of correlation tiles to process
 		const size_t      corr_stride_td,     // (in floats) stride for the input TD correlations
 		float           * gpu_corrs_td,       // correlation tiles in transform domain
+		float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
 		const size_t      corr_stride,        // in floats
 		float           * gpu_corrs,          // correlation output data (either pixel domain or transform domain
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,          // here - absolute, squared
 		int               corr_radius)        // radius of the output correlation (7 for 15x15)
 {
 	int corr_in_block = threadIdx.y;
@@ -1753,6 +1759,7 @@ extern "C" __global__ void corr2D_normalize_inner(
     __syncthreads();// __syncwarp();
     __shared__ float clt_corrs   [CORR_TILES_PER_BLOCK_NORMALIZE][4][DTT_SIZE][DTT_SIZE1];
     __shared__ float mlt_corrs   [CORR_TILES_PER_BLOCK_NORMALIZE][DTT_SIZE2M1][DTT_SIZE2M1]; // result correlation
+    __shared__ float norm_fat_zero [CORR_TILES_PER_BLOCK_NORMALIZE];
     // set clt_corr to all zeros
     float * clt_corr =  ((float *) clt_corrs) +  corr_in_block * (4 * DTT_SIZE * DTT_SIZE1); // top left quadrant0
     float * mclt_corr = ((float *) mlt_corrs) +  corr_in_block * (DTT_SIZE2M1*DTT_SIZE2M1);
@@ -1768,16 +1775,25 @@ extern "C" __global__ void corr2D_normalize_inner(
 	}
 	__syncthreads();// __syncwarp();
 
+	if (threadIdx.x == 0){
+		norm_fat_zero[corr_in_block] = fat_zero2;
+		if (corr_weights) { // same for all
+			norm_fat_zero[corr_in_block] /= * (corr_weights + corr_num);
+		}
+	}
+	__syncthreads();// __syncwarp();
+
+
 	// normalize Amplitude
 	normalizeTileAmplitude(
 			clt_corr, // float * clt_tile, //       [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
-			fat_zero); // float fat_zero ) // fat zero is absolute, scale it outside
+			norm_fat_zero[corr_in_block]); // fat_zero2); // float fat_zero2 ) // fat zero is absolute, scale it outside
 	// Low Pass Filter from constant area (is it possible to replace?)
 
 #ifdef DBG_TILE
 #ifdef DEBUG6
 	if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
-		printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero=%f\n",fat_zero);
+		printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero2=%f\n",fat_zero2);
 		debug_print_clt1(clt_corr, -1,  0xf);
 	}
 	__syncthreads();// __syncwarp();
@@ -3976,12 +3992,12 @@ __device__ void resetCorrelation(
  * Called from correlate2D()->correlate2D_inner()
  *
  * @param clt_tile             pointer to a correlation result tile [4][8][8+1] to be normalized
- * @param fat_zero             value to add to amplitudes for regularization. Absolute value,
+ * @param fat_zero2            value to add to amplitudes for regularization. Absolute value,
  *                             scale if needed outside.
  */
 __device__ void normalizeTileAmplitude(
 		float * clt_tile, //       [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
-		float fat_zero )  // fat zero is absolute, scale it outside
+		float fat_zero2 )  // fat zero is absolute, scale it outside
 {
 	int joffs = threadIdx.x * DTT_SIZE1;
 	float * clt_tile_j0 = clt_tile +    joffs;                // ==&clt_tile[0][j][0]
@@ -3990,7 +4006,7 @@ __device__ void normalizeTileAmplitude(
 	float * clt_tile_j3 = clt_tile_j2 + (DTT_SIZE1*DTT_SIZE); // ==&clt_tile[3][j][0]
 #pragma unroll
 	for (int i = 0; i < DTT_SIZE; i++) {
-		float s2 = fat_zero * fat_zero +
+		float s2 = fat_zero2 +
 				*(clt_tile_j0) * *(clt_tile_j0) +
 				*(clt_tile_j1) * *(clt_tile_j1) +
 				*(clt_tile_j2) * *(clt_tile_j2) +

src/TileProcessor.h

@@ -75,7 +75,7 @@ extern "C" __global__ void correlate2D(
 		float             scale0,             // scale for R
 		float             scale1,             // scale for B
 		float             scale2,             // scale for G
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,           // here - absolute, squared
 		float            * gpu_ftasks,         // flattened tasks, 29 floats for quad EO, 101 floats for LWIR16
 //		struct tp_task  * gpu_tasks,          // array of per-tile tasks (now bits 4..9 - correlation pairs)
 		int               num_tiles,          // number of tiles in task
@@ -90,9 +90,10 @@ extern "C" __global__ void corr2D_normalize(
 		int               num_corr_tiles,     // number of correlation tiles to process
 		const size_t      corr_stride_td,     // in floats
 		float           * gpu_corrs_td,       // correlation tiles in transform domain
+		float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
 		const size_t      corr_stride,        // in floats
 		float           * gpu_corrs,          // correlation output data (either pixel domain or transform domain
-		float             fat_zero,           // here - absolute
+		float             fat_zero2,          // here - absolute, squared
 		int               corr_radius);        // radius of the output correlation (7 for 15x15)
 
 extern "C" __global__ void corr2D_combine(

src/test_tp.cu

@@ -661,6 +661,7 @@ int main(int argc, char **argv)
 //#endif
     const char* result_corr_file =          "/home/eyesis/git/tile_processor_gpu/clt/aux_corr.corr";
     const char* result_corr_quad_file =     "/home/eyesis/git/tile_processor_gpu/clt/aux_corr-quad.corr";
+    const char* result_corr_td_norm_file =  "/home/eyesis/git/tile_processor_gpu/clt/aux_corr-td-norm.corr";
 ///    const char* result_corr_cross_file = "/home/eyesis/git/tile_processor_gpu/clt/aux_corr-cross.corr";
     const char* result_textures_file =      "/home/eyesis/git/tile_processor_gpu/clt/aux_texture_aux.rgba";
     const char* result_diff_rgb_combo_file ="/home/eyesis/git/tile_processor_gpu/clt/aux_diff_rgb_combo.drbg";
@@ -722,6 +723,7 @@ int main(int argc, char **argv)
 //#endif
     const char* result_corr_file = "/home/eyesis/git/tile_processor_gpu/clt/main_corr.corr";
     const char* result_corr_quad_file =  "/home/eyesis/git/tile_processor_gpu/clt/main_corr-quad.corr";
+    const char* result_corr_td_norm_file =  "/home/eyesis/git/tile_processor_gpu/clt/aux_corr-td-norm.corr";
 ///    const char* result_corr_cross_file = "/home/eyesis/git/tile_processor_gpu/clt/main_corr-cross.corr";
     const char* result_textures_file =       "/home/eyesis/git/tile_processor_gpu/clt/main_texture.rgba";
     const char* result_diff_rgb_combo_file ="/home/eyesis/git/tile_processor_gpu/clt/main_diff_rgb_combo.drbg";
@@ -978,25 +980,6 @@ int main(int argc, char **argv)
 			    (float *) &tile_coords_h[ncam],
 				ports_offs_xy_file[ncam]); // 			   char *  path) // file path
     }
-    /*
-    // build TP task that processes all tiles in linescan order
-    for (int ty = 0; ty < TILESY; ty++){
-        for (int tx = 0; tx < TILESX; tx++){
-            int nt = ty * TILESX + tx;
-            task_data[nt].task = 0xf | (((1 << NUM_PAIRS)-1) << TASK_CORR_BITS);
-            task_data[nt].txy = tx + (ty << 16);
-        //  for (int ncam = 0; ncam < NUM_CAMS; ncam++) {
-            for (int ncam = 0; ncam < num_cams; ncam++) {
-                task_data[nt].xy[ncam][0] = tile_coords_h[ncam][nt][0];
-                task_data[nt].xy[ncam][1] = tile_coords_h[ncam][nt][1];
-                task_data[nt].target_disparity = DBG_DISPARITY;
-            }
-        }
-    }
-
-    int tp_task_size =  sizeof(task_data)/sizeof(struct tp_task);
-    int num_active_tiles; // will be calculated by convert_direct
-    */
 
     for (int ty = 0; ty < TILESY; ty++){
         for (int tx = 0; tx < TILESX; tx++){
@@ -1019,80 +1002,19 @@ int main(int argc, char **argv)
 
     int tp_task_size =  TILESX * TILESY; // sizeof(ftask_data)/sizeof(float)/task_size; // number of task tiles
     int num_active_tiles; // will be calculated by convert_direct
+	int rslt_corr_size;
+	int corr_img_size;
 
-
-
-
-
-#ifdef DBG0
-//#define NUM_TEST_TILES 128
-#define NUM_TEST_TILES 1
-    for (int t = 0; t < NUM_TEST_TILES; t++) {
-    	task_data[t].task = 1;
-    	task_data[t].txy = ((DBG_TILE + t) - 324* ((DBG_TILE + t) / 324)) + (((DBG_TILE + t) / 324)) << 16;
-    	int nt = task_data[t].ty * TILESX + task_data[t].tx;
-
-//      for (int ncam = 0; ncam < NUM_CAMS; ncam++) {
-        for (int ncam = 0; ncam < num_cams; ncam++) {
-    		task_data[t].xy[ncam][0] = tile_coords_h[ncam][nt][0];
-    		task_data[t].xy[ncam][1] = tile_coords_h[ncam][nt][1];
-    	}
-    }
-    tp_task_size =  NUM_TEST_TILES; // sizeof(task_data)/sizeof(float);
-
-#endif
-
-    // segfault in the next
-///    gpu_tasks =  (struct tp_task  *) copyalloc_kernel_gpu((float * ) &task_data, tp_task_size * (sizeof(struct tp_task)/sizeof(float)));
-//    gpu_ftasks = (float  *) copyalloc_kernel_gpu((float * ) &ftask_data, tp_task_size * task_size); // (sizeof(struct tp_task)/sizeof(float)));
     gpu_ftasks = (float  *) copyalloc_kernel_gpu(ftask_data, tp_task_size * task_size); // (sizeof(struct tp_task)/sizeof(float)));
 
-    // build corr_indices - not needed anymore?
-    /*
-    num_corrs = 0;
-    for (int ty = 0; ty < TILESY; ty++){
-    	for (int tx = 0; tx < TILESX; tx++){
-    		int nt = ty * TILESX + tx;
-    		int cm = (task_data[nt].task >> TASK_CORR_BITS) & ((1 << NUM_PAIRS)-1);
-    		if (cm){
-    			for (int b = 0; b < NUM_PAIRS; b++) if ((cm & (1 << b)) != 0) {
-    				corr_indices[num_corrs++] = (nt << CORR_NTILE_SHIFT) | b;
-    			}
-    		}
-    	}
-    }
-    // num_corrs now has the total number of correlations
-    // copy corr_indices to gpu
-    gpu_corr_indices = (int  *) copyalloc_kernel_gpu(
-    		(float * ) corr_indices,
-			num_corrs,
-			NUM_PAIRS * TILESX * TILESY);
-    */
     // just allocate
     checkCudaErrors (cudaMalloc((void **)&gpu_corr_indices,        num_pairs * TILESX * TILESY*sizeof(int)));
     checkCudaErrors (cudaMalloc((void **)&gpu_corrs_combo_indices,             TILESX * TILESY*sizeof(int)));
-//
-
-    // build texture_indices
-    /*
-    num_textures = 0;
-    for (int ty = 0; ty < TILESY; ty++){
-    	for (int tx = 0; tx < TILESX; tx++){
-    		int nt = ty * TILESX + tx;
-    		int cm = task_data[nt].task & TASK_TEXTURE_BITS;
-    		if (cm){
-    			texture_indices[num_textures++] = (nt << CORR_NTILE_SHIFT) | (1 << LIST_TEXTURE_BIT);
-    		}
-    	}
-    }
-    */
     num_textures = 0;
     for (int ty = 0; ty < TILESY; ty++){
     	for (int tx = 0; tx < TILESX; tx++){
     		int nt = ty * TILESX + tx;
             float *tp = ftask_data + task_size * nt;
-
-//    		int cm = task_data[nt].task & TASK_TEXTURE_BITS;
     		int cm = (*(int *) tp) & TASK_TEXTURE_BITS;
     		if (cm){
     			texture_indices[num_textures++] = (nt << CORR_NTILE_SHIFT) | (1 << LIST_TEXTURE_BIT);
@@ -1153,6 +1075,15 @@ int main(int argc, char **argv)
     const int i0 = -1; // 0; // -1;
 #endif
 
+	int corr_size =        2 * CORR_OUT_RAD + 1;
+	int num_tiles = TILESX * TILESYA;
+	int num_corr_indices = num_pairs * num_tiles;
+
+	float * corr_img; //  = (float *)malloc(corr_img_size * sizeof(float));
+	float * cpu_corr; //  = (float *)malloc(rslt_corr_size * sizeof(float));
+	int * cpu_corr_indices; //  = (int *) malloc(num_corr_indices * sizeof(int));
+
+
 
 
 #define TEST_ROT_MATRICES
@@ -1561,7 +1492,7 @@ int main(int argc, char **argv)
 				color_weights[0], // 0.25,  // float             scale0,             // scale for R
 				color_weights[1], // 0.25,  // float             scale1,             // scale for B
 				color_weights[2], // 0.5,   // float             scale2,             // scale for G
-				30.0,                       // float             fat_zero,           // here - absolute
+				30.0 * 30.0,                // float             fat_zero2,           // here - absolute
 				gpu_ftasks,                 // float            * gpu_ftasks,         // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
 				tp_task_size,               // int               num_tiles) // number of tiles in task
 				TILESX,                     // int               tilesx,             // number of tile rows
@@ -1579,7 +1510,7 @@ int main(int argc, char **argv)
     sdkStopTimer(&timerCORR);
     float avgTimeCORR = (float)sdkGetTimerValue(&timerCORR) / (float)numIterations;
     sdkDeleteTimer(&timerCORR);
-//    printf("Average CORR run time =%f ms, num cor tiles (old) = %d\n",  avgTimeCORR, num_corrs);
+    //    printf("Average CORR run time =%f ms, num cor tiles (old) = %d\n",  avgTimeCORR, num_corrs);
 
     checkCudaErrors(cudaMemcpy(
     		&num_corrs,
@@ -1588,9 +1519,16 @@ int main(int argc, char **argv)
 			cudaMemcpyDeviceToHost));
     printf("Average CORR run time =%f ms, num cor tiles (new) = %d\n",  avgTimeCORR, num_corrs);
 
-    int corr_size =        2 * CORR_OUT_RAD + 1;
-    int rslt_corr_size =   num_corrs * corr_size * corr_size;
-    float * cpu_corr = (float *)malloc(rslt_corr_size * sizeof(float));
+//    int corr_size =        2 * CORR_OUT_RAD + 1;
+//    int rslt_corr_size =   num_corrs * corr_size * corr_size;
+//    float * cpu_corr = (float *)malloc(rslt_corr_size * sizeof(float));
+
+	rslt_corr_size =   num_corrs * corr_size * corr_size;
+	corr_img_size = num_corr_indices * 16*16; // NAN
+	corr_img = (float *)malloc(corr_img_size * sizeof(float));
+	cpu_corr = (float *)malloc(rslt_corr_size * sizeof(float));
+	cpu_corr_indices = (int *) malloc(num_corr_indices * sizeof(int));
+
 
     checkCudaErrors(cudaMemcpy2D(
     		cpu_corr,
@@ -1600,15 +1538,57 @@ int main(int argc, char **argv)
 			(corr_size * corr_size) * sizeof(float),
 			num_corrs,
 			cudaMemcpyDeviceToHost));
+    //    checkCudaErrors (cudaMalloc((void **)&gpu_corr_indices,        num_pairs * TILESX * TILESY*sizeof(int)));
+//    int num_tiles = TILESX * TILESYA;
+//   int num_corr_indices = num_pairs * num_tiles;
+//    int * cpu_corr_indices = (int *) malloc(num_corr_indices * sizeof(int));
+    checkCudaErrors(cudaMemcpy(
+    		cpu_corr_indices,
+			gpu_corr_indices,
+			num_corr_indices * sizeof(int),
+			cudaMemcpyDeviceToHost));
+//    int corr_img_size = num_corr_indices * 16*16; // NAN
+//    float * corr_img = (float *)malloc(corr_img_size * sizeof(float));
+    for (int i = 0; i < corr_img_size; i++){
+    	corr_img[i] = NAN;
+    }
+    for (int ict = 0; ict < num_corr_indices; ict++){
+    	//    	int ct = cpu_corr_indices[ict];
+    	int ctt = ( cpu_corr_indices[ict] >>  CORR_NTILE_SHIFT);
+    	int cpair = cpu_corr_indices[ict] & ((1 << CORR_NTILE_SHIFT) - 1);
+    	int ty = ctt / TILESX;
+    	int tx = ctt % TILESX;
+    	//		int src_offs0 = ict * num_pairs * corr_size * corr_size;
+    	int src_offs0 = ict * corr_size * corr_size;
+    	int dst_offs0 = cpair * (num_tiles * 16 * 16) +  (ty * 16 * TILESX * 16) + (tx * 16);
+
+    	for (int iy = 0; iy < corr_size; iy++){
+    		int src_offs = src_offs0 + iy * corr_size; // ict * num_pairs * corr_size * corr_size;
+    		int dst_offs = dst_offs0 + iy * (TILESX * 16);
+    		for (int ix = 0; ix < corr_size; ix++){
+    			corr_img[dst_offs++] = cpu_corr[src_offs++];
+    		}
+    	}
+    }
+    // num_pairs
 
 #ifndef NSAVE_CORR
-    		printf("Writing phase correlation data to %s\n",  result_corr_file);
+    printf("Writing phase correlation data to %s, width = %d, height=%d, slices=%d, length=%ld bytes\n",
+    		result_corr_file, (TILESX*16),(TILESYA*16), num_pairs, (corr_img_size * sizeof(float)) ) ;
+    /*
     		writeFloatsToFile(
     				cpu_corr,    // float *       data, // allocated array
 					rslt_corr_size,    // int           size, // length in elements
 					result_corr_file); // 			   const char *  path) // file path
+     */
+    writeFloatsToFile(
+    		corr_img,    // float *       data, // allocated array
+			corr_img_size,    // int           size, // length in elements
+			result_corr_file); // 			   const char *  path) // file path
 #endif
-    		free(cpu_corr);
+    free (cpu_corr);
+    free (cpu_corr_indices);
+    free (corr_img);
 #endif // ifndef NOCORR
 
 #ifndef NOCORR_TD
@@ -1637,7 +1617,7 @@ int main(int argc, char **argv)
 				color_weights[0], // 0.25,     // float             scale0,             // scale for R
 				color_weights[1], // 0.25,     // float             scale1,             // scale for B
 				color_weights[2], // 0.5,      // float             scale2,             // scale for G
-				30.0,                          // float             fat_zero,           // here - absolute
+				30.0*30.0,                     // float             fat_zero2,          // here - absolute (squared)
 				gpu_ftasks,                    // float            * gpu_ftasks,        // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
 				tp_task_size,                  // int               num_tiles) // number of tiles in task
 				TILESX,                        // int               tilesx,             // number of tile rows
@@ -1655,8 +1635,9 @@ int main(int argc, char **argv)
     			gpu_num_corr_tiles,
     			sizeof(int),
     			cudaMemcpyDeviceToHost));
-    	num_corr_combo = num_corrs/num_pairs;
 
+#ifdef QUAD_COMBINE
+    	num_corr_combo = num_corrs/num_pairs;
     	corr2D_combine<<<1,1>>>( // Combine quad (2 hor, 2 vert) pairs
     			num_corr_combo, // tp_task_size,     // int               num_tiles,          // number of tiles to process (each with num_pairs)
 				num_pairs,                           // int               num_pairs,          // num pairs per tile (should be the same)
@@ -1677,11 +1658,24 @@ int main(int argc, char **argv)
     			num_corr_combo, //tp_task_size,      // int               num_corr_tiles,     // number of correlation tiles to process
 				dstride_corr_combo_td/sizeof(float), // const size_t      corr_stride_td,     // in floats
 				gpu_corrs_combo_td,                  // float           * gpu_corrs_td,       // correlation tiles in transform domain
+				(float *) 0, // corr_weights,                  // float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
 				dstride_corr_combo/sizeof(float),    // const size_t      corr_stride,        // in floats
 				gpu_corrs_combo,                     // float           * gpu_corrs,          // correlation output data (pixel domain)
-				30.0,                                // float             fat_zero,           // here - absolute
+				30.0 * 30.0,                         // float             fat_zero2,           // here - absolute
 				CORR_OUT_RAD);                       // int               corr_radius);        // radius of the output correlation (7 for 15x15)
+#else
+    	checkCudaErrors(cudaDeviceSynchronize());
 
+    	corr2D_normalize<<<1,1>>>(
+    			num_corrs, //tp_task_size,           // int               num_corr_tiles,     // number of correlation tiles to process
+				dstride_corr_td/sizeof(float),       // const size_t      corr_stride_td,     // in floats
+				gpu_corrs_td,                        // float           * gpu_corrs_td,       // correlation tiles in transform domain
+				(float *) 0, // corr_weights,        // float           * corr_weights,       // null or per-tile weight (fat_zero2 will be divided by it)
+				dstride_corr/sizeof(float),          // const size_t      corr_stride,        // in floats
+				gpu_corrs,                           // float           * gpu_corrs,          // correlation output data (pixel domain)
+				30.0 * 30.0,                         // float             fat_zero2,           // here - absolute
+				CORR_OUT_RAD);                       // int               corr_radius);        // radius of the output correlation (7 for 15x15)
+#endif
     	getLastCudaError("Kernel failure:corr2D_normalize");
     	checkCudaErrors(cudaDeviceSynchronize());
     	printf("corr2D_normalize pass: %d\n",i);
@@ -1691,8 +1685,9 @@ int main(int argc, char **argv)
     sdkStopTimer(&timerCORRTD);
     float avgTimeCORRTD = (float)sdkGetTimerValue(&timerCORRTD) / (float)numIterations;
     sdkDeleteTimer(&timerCORRTD);
-    printf("Average CORR-TD and companions run time =%f ms, num cor tiles (old) = %d\n",  avgTimeCORR, num_corrs);
+    printf("Average CORR-TD and companions run time =%f ms, num cor tiles (old) = %d\n",  avgTimeCORRTD, num_corrs);
 
+#ifdef QUAD_COMBINE
     int corr_size_combo =        2 * CORR_OUT_RAD + 1;
     int rslt_corr_size_combo =   num_corr_combo * corr_size_combo * corr_size_combo;
     float * cpu_corr_combo =    (float *)malloc(rslt_corr_size_combo * sizeof(float));
@@ -1705,8 +1700,8 @@ int main(int argc, char **argv)
 			(corr_size_combo * corr_size_combo) * sizeof(float),
 			num_corr_combo,
 			cudaMemcpyDeviceToHost));
-//    const char* result_corr_quad_file =  "/home/eyesis/git/tile_processor_gpu/clt/main_corr-quad.corr";
-//    const char* result_corr_cross_file = "/home/eyesis/git/tile_processor_gpu/clt/main_corr-cross.corr";
+    //    const char* result_corr_quad_file =  "/home/eyesis/git/tile_processor_gpu/clt/main_corr-quad.corr";
+    //    const char* result_corr_cross_file = "/home/eyesis/git/tile_processor_gpu/clt/main_corr-cross.corr";
 
 #ifndef NSAVE_CORR
     printf("Writing phase correlation data to %s\n",  result_corr_quad_file);
@@ -1716,8 +1711,85 @@ int main(int argc, char **argv)
 			result_corr_quad_file); // 			     const char *  path) // file path
 #endif
     free(cpu_corr_combo);
-#endif // ifndef NOCORR_TD
 
+#else // QUAD_COMBINE
+    // Reading / formatting / saving 	correlate2D(TD) + corr2D_normalize
+
+    checkCudaErrors(cudaMemcpy(
+    		&num_corrs,
+			gpu_num_corr_tiles,
+			sizeof(int),
+			cudaMemcpyDeviceToHost));
+  //  printf("Average CORR run time =%f ms, num cor tiles (new) = %d\n",  avgTimeCORR, num_corrs);
+
+//    int corr_size =        2 * CORR_OUT_RAD + 1;
+//    int rslt_corr_size =   num_corrs * corr_size * corr_size;
+//    float * cpu_corr = (float *)malloc(rslt_corr_size * sizeof(float));
+
+	rslt_corr_size =   num_corrs * corr_size * corr_size;
+	corr_img_size = num_corr_indices * 16*16; // NAN
+	corr_img = (float *)malloc(corr_img_size * sizeof(float));
+	cpu_corr = (float *)malloc(rslt_corr_size * sizeof(float));
+	cpu_corr_indices = (int *) malloc(num_corr_indices * sizeof(int));
+
+
+
+    checkCudaErrors(cudaMemcpy2D(
+    		cpu_corr,
+			(corr_size * corr_size) * sizeof(float),
+			gpu_corrs,
+			dstride_corr,
+			(corr_size * corr_size) * sizeof(float),
+			num_corrs,
+			cudaMemcpyDeviceToHost));
+    //    checkCudaErrors (cudaMalloc((void **)&gpu_corr_indices,        num_pairs * TILESX * TILESY*sizeof(int)));
+//    int num_tiles = TILESX * TILESYA;
+//    int num_corr_indices = num_pairs * num_tiles;
+//    int * cpu_corr_indices = (int *) malloc(num_corr_indices * sizeof(int));
+    checkCudaErrors(cudaMemcpy(
+    		cpu_corr_indices,
+			gpu_corr_indices,
+			num_corr_indices * sizeof(int),
+			cudaMemcpyDeviceToHost));
+//    int corr_img_size = num_corr_indices * 16*16; // NAN
+//    float * corr_img = (float *)malloc(corr_img_size * sizeof(float));
+    for (int i = 0; i < corr_img_size; i++){
+    	corr_img[i] = NAN;
+    }
+    for (int ict = 0; ict < num_corr_indices; ict++){
+    	//    	int ct = cpu_corr_indices[ict];
+    	int ctt = ( cpu_corr_indices[ict] >>  CORR_NTILE_SHIFT);
+    	int cpair = cpu_corr_indices[ict] & ((1 << CORR_NTILE_SHIFT) - 1);
+    	int ty = ctt / TILESX;
+    	int tx = ctt % TILESX;
+    	//		int src_offs0 = ict * num_pairs * corr_size * corr_size;
+    	int src_offs0 = ict * corr_size * corr_size;
+    	int dst_offs0 = cpair * (num_tiles * 16 * 16) +  (ty * 16 * TILESX * 16) + (tx * 16);
+
+    	for (int iy = 0; iy < corr_size; iy++){
+    		int src_offs = src_offs0 + iy * corr_size; // ict * num_pairs * corr_size * corr_size;
+    		int dst_offs = dst_offs0 + iy * (TILESX * 16);
+    		for (int ix = 0; ix < corr_size; ix++){
+    			corr_img[dst_offs++] = cpu_corr[src_offs++];
+    		}
+    	}
+    }
+    // num_pairs
+
+#ifndef NSAVE_CORR
+    printf("Writing phase correlation data to %s, width = %d, height=%d, slices=%d, length=%ld bytes\n",
+    		result_corr_file, (TILESX*16),(TILESYA*16), num_pairs, (corr_img_size * sizeof(float)) ) ;
+    writeFloatsToFile(
+    		corr_img,                  // float *       data, // allocated array
+			corr_img_size,             // int           size, // length in elements
+			result_corr_td_norm_file); // 			   const char *  path) // file path
+#endif
+    free (cpu_corr);
+    free (cpu_corr_indices);
+    free (corr_img);
+
+#endif // // QUAD_COMBINE#else
+#endif // ifndef NOCORR_TD