/* nlmeans.c Copyright (c) 2013 Dirk Farin Copyright (c) 2003-2016 HandBrake Team This file is part of the HandBrake source code Homepage: . It may be used under the terms of the GNU General Public License v2. For full terms see the file COPYING file or visit http://www.gnu.org/licenses/gpl-2.0.html */ /* Usage * * Parameters: * lumaY_strength : lumaY_origin_tune : lumaY_patch_size : lumaY_range : lumaY_frames : lumaY_prefilter : * chromaB_strength : chromaB_origin_tune : chromaB_patch_size : chromaB_range : chromaB_frames : chromaB_prefilter : * chromaR_strength : chromaR_origin_tune : chromaR_patch_size : chromaR_range : chromaR_frames : chromaR_prefilter * * Defaults: * 8:1:7:3:2:0 for each channel (equivalent to 8:1:7:3:2:0:8:1:7:3:2:0:8:1:7:3:2:0) * * Parameters cascade, e.g. 6:0.8:7:3:3:0:4:1 sets: * strength 6, origin tune 0.8 for luma * patch size 7, range 3, frames 3, prefilter 0 for all channels * strength 4, origin tune 1 for both chroma channels * * Strength is relative and must be adjusted; ALL parameters affect overall strength. * Lower origin tune improves results for noisier input or animation (film 0.5-1, animation 0.15-0.5). * Large patch size (>9) may greatly reduce quality by clobbering detail. * Larger search range increases quality; however, computation time increases exponentially. * Large number of frames (film >3, animation >6) may cause temporal smearing. * Prefiltering can potentially improve weight decisions, yielding better results for difficult sources. * * Prefilter enum combos: * 1: Mean 3x3 * 2: Mean 5x5 * 3: Mean 5x5 (overrides Mean 3x3) * 257: Mean 3x3 reduced by 25% * 258: Mean 5x5 reduced by 25% * 513: Mean 3x3 reduced by 50% * 514: Mean 5x5 reduced by 50% * 769: Mean 3x3 reduced by 75% * 770: Mean 5x5 reduced by 75% * 1025: Mean 3x3 plus edge boost (restores lost edge detail) * 1026: Mean 5x5 plus edge boost * 1281: Mean 3x3 reduced by 25% plus edge boost * etc... * 2049: Mean 3x3 passthru (NLMeans off, prefilter is the output) * etc... * 3329: Mean 3x3 reduced by 25% plus edge boost, passthru * etc... */ #include "hb.h" #include "hbffmpeg.h" #include "taskset.h" #include "nlmeans.h" #define NLMEANS_STRENGTH_LUMA_DEFAULT 6 #define NLMEANS_STRENGTH_CHROMA_DEFAULT 6 #define NLMEANS_ORIGIN_TUNE_LUMA_DEFAULT 1 #define NLMEANS_ORIGIN_TUNE_CHROMA_DEFAULT 1 #define NLMEANS_PATCH_SIZE_LUMA_DEFAULT 7 #define NLMEANS_PATCH_SIZE_CHROMA_DEFAULT 7 #define NLMEANS_RANGE_LUMA_DEFAULT 3 #define NLMEANS_RANGE_CHROMA_DEFAULT 3 #define NLMEANS_FRAMES_LUMA_DEFAULT 2 #define NLMEANS_FRAMES_CHROMA_DEFAULT 2 #define NLMEANS_PREFILTER_LUMA_DEFAULT 0 #define NLMEANS_PREFILTER_CHROMA_DEFAULT 0 #define NLMEANS_PREFILTER_MODE_MEAN3X3 1 #define NLMEANS_PREFILTER_MODE_MEAN5X5 2 #define NLMEANS_PREFILTER_MODE_MEDIAN3X3 4 #define NLMEANS_PREFILTER_MODE_MEDIAN5X5 8 #define NLMEANS_PREFILTER_MODE_RESERVED16 16 // Reserved #define NLMEANS_PREFILTER_MODE_RESERVED32 32 // Reserved #define NLMEANS_PREFILTER_MODE_RESERVED64 64 // Reserved #define NLMEANS_PREFILTER_MODE_RESERVED128 128 // Reserved #define NLMEANS_PREFILTER_MODE_REDUCE25 256 #define NLMEANS_PREFILTER_MODE_REDUCE50 512 #define NLMEANS_PREFILTER_MODE_EDGEBOOST 1024 #define NLMEANS_PREFILTER_MODE_PASSTHRU 2048 #define NLMEANS_SORT(a,b) { if (a > b) NLMEANS_SWAP(a, b); } #define NLMEANS_SWAP(a,b) { a = (a ^ b); b = (a ^ b); a = (b ^ a); } #define NLMEANS_FRAMES_MAX 32 #define NLMEANS_EXPSIZE 128 typedef struct { uint8_t *mem; uint8_t *mem_pre; uint8_t *image; uint8_t *image_pre; int w; int h; int border; hb_lock_t *mutex; int prefiltered; } BorderedPlane; typedef struct { int width; int height; int fmt; BorderedPlane plane[3]; hb_buffer_settings_t s; } Frame; struct PixelSum { float weight_sum; float pixel_sum; }; typedef struct { hb_filter_private_t *pv; int segment; hb_buffer_t *out; } nlmeans_thread_arg_t; struct hb_filter_private_s { double strength[3]; // averaging weight decay, larger produces smoother output double origin_tune[3]; // weight tuning for origin patch, 0.00..1.00 int patch_size[3]; // pixel context region width (must be odd) int range[3]; // spatial search window width (must be odd) int nframes[3]; // temporal search depth in frames int prefilter[3]; // prefilter mode, can improve weight analysis float exptable[3][NLMEANS_EXPSIZE]; float weight_fact_table[3]; int diff_max[3]; NLMeansFunctions functions; Frame *frame; int next_frame; int max_frames; taskset_t taskset; int thread_count; nlmeans_thread_arg_t **thread_data; }; static int nlmeans_init(hb_filter_object_t *filter, hb_filter_init_t *init); static int nlmeans_work(hb_filter_object_t *filter, hb_buffer_t **buf_in, hb_buffer_t **buf_out); static void nlmeans_close(hb_filter_object_t *filter); static void nlmeans_filter_thread(void *thread_args_v); static const char nlmeans_template[] = "y-strength=^"HB_FLOAT_REG"$:y-origin-tune=^"HB_FLOAT_REG"$:" "y-patch-size=^"HB_INT_REG"$:y-range=^"HB_INT_REG"$:" "y-frame-count=^"HB_INT_REG"$:y-prefilter=^"HB_INT_REG"$:" "cb-strength=^"HB_FLOAT_REG"$:cb-origin-tune=^"HB_FLOAT_REG"$:" "cb-patch-size=^"HB_INT_REG"$:cb-range=^"HB_INT_REG"$:" "cb-frame-count=^"HB_INT_REG"$:cb-prefilter=^"HB_INT_REG"$:" "cr-strength=^"HB_FLOAT_REG"$:cr-origin-tune=^"HB_FLOAT_REG"$:" "cr-patch-size=^"HB_INT_REG"$:cr-range=^"HB_INT_REG"$:" "cr-frame-count=^"HB_INT_REG"$:cr-prefilter=^"HB_INT_REG"$"; hb_filter_object_t hb_filter_nlmeans = { .id = HB_FILTER_NLMEANS, .enforce_order = 1, .name = "Denoise (nlmeans)", .settings = NULL, .init = nlmeans_init, .work = nlmeans_work, .close = nlmeans_close, .settings_template = nlmeans_template, }; static void nlmeans_border(uint8_t *src, const int w, const int h, const int border) { const int bw = w + 2 * border; uint8_t *image = src + border + bw * border; // Create faux borders using edge pixels for (int y = 0; y < h; y++) { for (int x = 0; x < border; x++) { *(image + y*bw - x - 1) = *(image + y*bw + x); *(image + y*bw + x + w) = *(image + y*bw - x + (w-1)); } } for (int y = 0; y < border; y++) { memcpy(image - border - (y+1)*bw, image - border + y*bw, bw); memcpy(image - border + (y+h)*bw, image - border + (h-y-1)*bw, bw); } } static void nlmeans_deborder(const BorderedPlane *src, uint8_t *dst, const int w, const int s, const int h) { const int bw = src->w + 2 * src->border; uint8_t *image = src->mem + src->border + bw * src->border; int width = w; if (src->w < width) { width = src->w; } // Copy main image for (int y = 0; y < h; y++) { memcpy(dst + y * s, image + y * bw, width); } } static void nlmeans_alloc(const uint8_t *src, const int src_w, const int src_s, const int src_h, BorderedPlane *dst, const int border) { const int bw = src_w + 2 * border; const int bh = src_h + 2 * border; uint8_t *mem = malloc(bw * bh * sizeof(uint8_t)); uint8_t *image = mem + border + bw * border; // Copy main image for (int y = 0; y < src_h; y++) { memcpy(image + y * bw, src + y * src_s, src_w); } dst->mem = mem; dst->image = image; dst->w = src_w; dst->h = src_h; dst->border = border; nlmeans_border(dst->mem, dst->w, dst->h, dst->border); dst->mem_pre = dst->mem; dst->image_pre = dst->image; } static void nlmeans_filter_mean(const uint8_t *src, uint8_t *dst, const int w, const int h, const int border, const int size) { // Mean filter const int bw = w + 2 * border; const int offset_min = -((size - 1) /2); const int offset_max = (size + 1) /2; const double pixel_weight = 1.0 / (size * size); uint16_t pixel_sum; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { pixel_sum = 0; for (int k = offset_min; k < offset_max; k++) { for (int j = offset_min; j < offset_max; j++) { pixel_sum = pixel_sum + *(src + bw*(y+j) + (x+k)); } } *(dst + bw*y + x) = (uint8_t)(pixel_sum * pixel_weight); } } } static uint8_t nlmeans_filter_median_opt(uint8_t *pixels, const int size) { // Optimized sorting networks if (size == 3) { /* opt_med9() via Nicolas Devillard * http://ndevilla.free.fr/median/median.pdf */ NLMEANS_SORT(pixels[1], pixels[2]); NLMEANS_SORT(pixels[4], pixels[5]); NLMEANS_SORT(pixels[7], pixels[8]); NLMEANS_SORT(pixels[0], pixels[1]); NLMEANS_SORT(pixels[3], pixels[4]); NLMEANS_SORT(pixels[6], pixels[7]); NLMEANS_SORT(pixels[1], pixels[2]); NLMEANS_SORT(pixels[4], pixels[5]); NLMEANS_SORT(pixels[7], pixels[8]); NLMEANS_SORT(pixels[0], pixels[3]); NLMEANS_SORT(pixels[5], pixels[8]); NLMEANS_SORT(pixels[4], pixels[7]); NLMEANS_SORT(pixels[3], pixels[6]); NLMEANS_SORT(pixels[1], pixels[4]); NLMEANS_SORT(pixels[2], pixels[5]); NLMEANS_SORT(pixels[4], pixels[7]); NLMEANS_SORT(pixels[4], pixels[2]); NLMEANS_SORT(pixels[6], pixels[4]); NLMEANS_SORT(pixels[4], pixels[2]); return pixels[4]; } else if (size == 5) { /* opt_med25() via Nicolas Devillard * http://ndevilla.free.fr/median/median.pdf */ NLMEANS_SORT(pixels[0], pixels[1]); NLMEANS_SORT(pixels[3], pixels[4]); NLMEANS_SORT(pixels[2], pixels[4]); NLMEANS_SORT(pixels[2], pixels[3]); NLMEANS_SORT(pixels[6], pixels[7]); NLMEANS_SORT(pixels[5], pixels[7]); NLMEANS_SORT(pixels[5], pixels[6]); NLMEANS_SORT(pixels[9], pixels[10]); NLMEANS_SORT(pixels[8], pixels[10]); NLMEANS_SORT(pixels[8], pixels[9]); NLMEANS_SORT(pixels[12], pixels[13]); NLMEANS_SORT(pixels[11], pixels[13]); NLMEANS_SORT(pixels[11], pixels[12]); NLMEANS_SORT(pixels[15], pixels[16]); NLMEANS_SORT(pixels[14], pixels[16]); NLMEANS_SORT(pixels[14], pixels[15]); NLMEANS_SORT(pixels[18], pixels[19]); NLMEANS_SORT(pixels[17], pixels[19]); NLMEANS_SORT(pixels[17], pixels[18]); NLMEANS_SORT(pixels[21], pixels[22]); NLMEANS_SORT(pixels[20], pixels[22]); NLMEANS_SORT(pixels[20], pixels[21]); NLMEANS_SORT(pixels[23], pixels[24]); NLMEANS_SORT(pixels[2], pixels[5]); NLMEANS_SORT(pixels[3], pixels[6]); NLMEANS_SORT(pixels[0], pixels[6]); NLMEANS_SORT(pixels[0], pixels[3]); NLMEANS_SORT(pixels[4], pixels[7]); NLMEANS_SORT(pixels[1], pixels[7]); NLMEANS_SORT(pixels[1], pixels[4]); NLMEANS_SORT(pixels[11], pixels[14]); NLMEANS_SORT(pixels[8], pixels[14]); NLMEANS_SORT(pixels[8], pixels[11]); NLMEANS_SORT(pixels[12], pixels[15]); NLMEANS_SORT(pixels[9], pixels[15]); NLMEANS_SORT(pixels[9], pixels[12]); NLMEANS_SORT(pixels[13], pixels[16]); NLMEANS_SORT(pixels[10], pixels[16]); NLMEANS_SORT(pixels[10], pixels[13]); NLMEANS_SORT(pixels[20], pixels[23]); NLMEANS_SORT(pixels[17], pixels[23]); NLMEANS_SORT(pixels[17], pixels[20]); NLMEANS_SORT(pixels[21], pixels[24]); NLMEANS_SORT(pixels[18], pixels[24]); NLMEANS_SORT(pixels[18], pixels[21]); NLMEANS_SORT(pixels[19], pixels[22]); NLMEANS_SORT(pixels[8], pixels[17]); NLMEANS_SORT(pixels[9], pixels[18]); NLMEANS_SORT(pixels[0], pixels[18]); NLMEANS_SORT(pixels[0], pixels[9]); NLMEANS_SORT(pixels[10], pixels[19]); NLMEANS_SORT(pixels[1], pixels[19]); NLMEANS_SORT(pixels[1], pixels[10]); NLMEANS_SORT(pixels[11], pixels[20]); NLMEANS_SORT(pixels[2], pixels[20]); NLMEANS_SORT(pixels[2], pixels[11]); NLMEANS_SORT(pixels[12], pixels[21]); NLMEANS_SORT(pixels[3], pixels[21]); NLMEANS_SORT(pixels[3], pixels[12]); NLMEANS_SORT(pixels[13], pixels[22]); NLMEANS_SORT(pixels[4], pixels[22]); NLMEANS_SORT(pixels[4], pixels[13]); NLMEANS_SORT(pixels[14], pixels[23]); NLMEANS_SORT(pixels[5], pixels[23]); NLMEANS_SORT(pixels[5], pixels[14]); NLMEANS_SORT(pixels[15], pixels[24]); NLMEANS_SORT(pixels[6], pixels[24]); NLMEANS_SORT(pixels[6], pixels[15]); NLMEANS_SORT(pixels[7], pixels[16]); NLMEANS_SORT(pixels[7], pixels[19]); NLMEANS_SORT(pixels[13], pixels[21]); NLMEANS_SORT(pixels[15], pixels[23]); NLMEANS_SORT(pixels[7], pixels[13]); NLMEANS_SORT(pixels[7], pixels[15]); NLMEANS_SORT(pixels[1], pixels[9]); NLMEANS_SORT(pixels[3], pixels[11]); NLMEANS_SORT(pixels[5], pixels[17]); NLMEANS_SORT(pixels[11], pixels[17]); NLMEANS_SORT(pixels[9], pixels[17]); NLMEANS_SORT(pixels[4], pixels[10]); NLMEANS_SORT(pixels[6], pixels[12]); NLMEANS_SORT(pixels[7], pixels[14]); NLMEANS_SORT(pixels[4], pixels[6]); NLMEANS_SORT(pixels[4], pixels[7]); NLMEANS_SORT(pixels[12], pixels[14]); NLMEANS_SORT(pixels[10], pixels[14]); NLMEANS_SORT(pixels[6], pixels[7]); NLMEANS_SORT(pixels[10], pixels[12]); NLMEANS_SORT(pixels[6], pixels[10]); NLMEANS_SORT(pixels[6], pixels[17]); NLMEANS_SORT(pixels[12], pixels[17]); NLMEANS_SORT(pixels[7], pixels[17]); NLMEANS_SORT(pixels[7], pixels[10]); NLMEANS_SORT(pixels[12], pixels[18]); NLMEANS_SORT(pixels[7], pixels[12]); NLMEANS_SORT(pixels[10], pixels[18]); NLMEANS_SORT(pixels[12], pixels[20]); NLMEANS_SORT(pixels[10], pixels[20]); NLMEANS_SORT(pixels[10], pixels[12]); return pixels[12]; } // Network for size not implemented return pixels[(int)((size * size)/2)]; } static void nlmeans_filter_median(const uint8_t *src, uint8_t *dst, const int w, const int h, const int border, const int size) { // Median filter const int bw = w + 2 * border; const int offset_min = -((size - 1) /2); const int offset_max = (size + 1) /2; int index; uint8_t pixels[size * size]; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { index = 0; for (int k = offset_min; k < offset_max; k++) { for (int j = offset_min; j < offset_max; j++) { pixels[index] = *(src + bw*(y+j) + (x+k)); index++; } } *(dst + bw*y + x) = nlmeans_filter_median_opt(pixels, size); } } } static void nlmeans_filter_edgeboost(const uint8_t *src, uint8_t *dst, const int w, const int h, const int border) { const int bw = w + 2 * border; const int bh = h + 2 * border; // Custom kernel const int kernel_size = 3; const int kernel[3][3] = {{-31, 0, 31}, {-44, 0, 44}, {-31, 0, 31}}; const double kernel_coef = 1.0 / 126.42; // Detect edges const int offset_min = -((kernel_size - 1) /2); const int offset_max = (kernel_size + 1) /2; uint16_t pixel1; uint16_t pixel2; uint8_t *mask_mem = calloc(bw * bh, sizeof(uint8_t)); uint8_t *mask = mask_mem + border + bw * border; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { pixel1 = 0; pixel2 = 0; for (int k = offset_min; k < offset_max; k++) { for (int j = offset_min; j < offset_max; j++) { pixel1 += kernel[j+1][k+1] * *(src + bw*(y+j) + (x+k)); pixel2 += kernel[k+1][j+1] * *(src + bw*(y+j) + (x+k)); } } pixel1 = pixel1 > 0 ? pixel1 : -pixel1; pixel2 = pixel2 > 0 ? pixel2 : -pixel2; pixel1 = (uint16_t)(((double)pixel1 * kernel_coef) + 128); pixel2 = (uint16_t)(((double)pixel2 * kernel_coef) + 128); *(mask + bw*y + x) = (uint8_t)(pixel1 + pixel2); if (*(mask + bw*y + x) > 160) { *(mask + bw*y + x) = 235; } else if (*(mask + bw*y + x) > 16) { *(mask + bw*y + x) = 128; } else { *(mask + bw*y + x) = 16; } } } // Post-process and output int pixels; for (int y = 0; y < h; y++) { for (int x = 0; x < w; x++) { if (*(mask + bw*y + x) > 16) { // Count nearby edge pixels pixels = 0; for (int k = offset_min; k < offset_max; k++) { for (int j = offset_min; j < offset_max; j++) { if (*(mask + bw*(y+j) + (x+k)) > 16) { pixels++; } } } // Remove false positive if (pixels < 3) { *(mask + bw*y + x) = 16; } // Filter output if (*(mask + bw*y + x) > 16) { if (*(mask + bw*y + x) == 235) { *(dst + bw*y + x) = (3 * *(src + bw*y + x) + 1 * *(dst + bw*y + x)) /4; } else { *(dst + bw*y + x) = (2 * *(src + bw*y + x) + 3 * *(dst + bw*y + x)) /5; } //*(dst + bw*y + x) = *(mask + bw*y + x); // Overlay mask } } //*(dst + bw*y + x) = *(mask + bw*y + x); // Full mask } } free(mask_mem); } static void nlmeans_prefilter(BorderedPlane *src, const int filter_type) { hb_lock(src->mutex); if (src->prefiltered) { hb_unlock(src->mutex); return; } if (filter_type & NLMEANS_PREFILTER_MODE_MEAN3X3 || filter_type & NLMEANS_PREFILTER_MODE_MEAN5X5 || filter_type & NLMEANS_PREFILTER_MODE_MEDIAN3X3 || filter_type & NLMEANS_PREFILTER_MODE_MEDIAN5X5) { // Source image const uint8_t *mem = src->mem; const uint8_t *image = src->image; const int border = src->border; const int w = src->w; const int h = src->h; const int bw = w + 2 * border; const int bh = h + 2 * border; // Duplicate plane uint8_t *mem_pre = malloc(bw * bh * sizeof(uint8_t)); uint8_t *image_pre = mem_pre + border + bw * border; for (int y = 0; y < h; y++) { memcpy(mem_pre + y * bw, mem + y * bw, bw); } // Filter plane; should already have at least 2px extra border on each side if (filter_type & NLMEANS_PREFILTER_MODE_MEDIAN5X5) { // Median 5x5 nlmeans_filter_median(image, image_pre, w, h, border, 5); } else if (filter_type & NLMEANS_PREFILTER_MODE_MEDIAN3X3) { // Median 3x3 nlmeans_filter_median(image, image_pre, w, h, border, 3); } else if (filter_type & NLMEANS_PREFILTER_MODE_MEAN5X5) { // Mean 5x5 nlmeans_filter_mean(image, image_pre, w, h, border, 5); } else if (filter_type & NLMEANS_PREFILTER_MODE_MEAN3X3) { // Mean 3x3 nlmeans_filter_mean(image, image_pre, w, h, border, 3); } // Restore edges if (filter_type & NLMEANS_PREFILTER_MODE_EDGEBOOST) { nlmeans_filter_edgeboost(image, image_pre, w, h, border); } // Blend source and destination for lesser effect int wet = 1; int dry = 0; if (filter_type & NLMEANS_PREFILTER_MODE_REDUCE50 && filter_type & NLMEANS_PREFILTER_MODE_REDUCE25) { wet = 1; dry = 3; } else if (filter_type & NLMEANS_PREFILTER_MODE_REDUCE50) { wet = 1; dry = 1; } else if (filter_type & NLMEANS_PREFILTER_MODE_REDUCE25) { wet = 3; dry = 1; } if (dry > 0) { for (int y = 0; y < bh; y++) { for (int x = 0; x < bw; x++) { *(mem_pre + bw*y + x) = (uint8_t)((wet * *(mem_pre + bw*y + x) + dry * *(mem + bw*y + x)) / (wet + dry)); } } } // Assign result src->mem_pre = mem_pre; src->image_pre = image_pre; // Recreate borders nlmeans_border(mem_pre, w, h, border); } src->prefiltered = 1; hb_unlock(src->mutex); } static void build_integral_scalar(uint32_t *integral, int integral_stride, const uint8_t *src, const uint8_t *src_pre, const uint8_t *compare, const uint8_t *compare_pre, int w, int border, int dst_w, int dst_h, int dx, int dy) { const int bw = w + 2 * border; for (int y = 0; y < dst_h; y++) { const uint8_t *p1 = src_pre + y*bw; const uint8_t *p2 = compare_pre + (y+dy)*bw + dx; uint32_t *out = integral + (y*integral_stride); for (int x = 0; x < dst_w; x++) { int diff = *p1 - *p2; *out = *(out-1) + diff * diff; out++; p1++; p2++; } if (y > 0) { out = integral + y*integral_stride; for (int x = 0; x < dst_w; x++) { *out += *(out - integral_stride); out++; } } } } static void nlmeans_plane(NLMeansFunctions *functions, Frame *frame, int prefilter, int plane, int nframes, uint8_t *dst, int dst_w, int dst_s, int dst_h, double h_param, double origin_tune, int n, int r, const float *exptable, const float weight_fact_table, const int diff_max) { const int n_half = (n-1) /2; const int r_half = (r-1) /2; // Source image const uint8_t *src = frame[0].plane[plane].image; const uint8_t *src_pre = frame[0].plane[plane].image_pre; const int w = frame[0].plane[plane].w; const int border = frame[0].plane[plane].border; const int bw = w + 2 * border; // Allocate temporary pixel sums struct PixelSum *tmp_data = calloc(dst_w * dst_h, sizeof(struct PixelSum)); // Allocate integral image const int integral_stride = ((dst_w + 15) / 16 * 16) + 2 * 16; uint32_t* const integral_mem = calloc(integral_stride * (dst_h+1), sizeof(uint32_t)); uint32_t* const integral = integral_mem + integral_stride + 16; // Iterate through available frames for (int f = 0; f < nframes; f++) { nlmeans_prefilter(&frame[f].plane[plane], prefilter); // Compare image const uint8_t *compare = frame[f].plane[plane].image; const uint8_t *compare_pre = frame[f].plane[plane].image_pre; // Iterate through all displacements for (int dy = -r_half; dy <= r_half; dy++) { for (int dx = -r_half; dx <= r_half; dx++) { // Apply special weight tuning to origin patch if (dx == 0 && dy == 0 && f == 0) { // TODO: Parallelize this for (int y = n_half; y < dst_h-n + n_half; y++) { for (int x = n_half; x < dst_w-n + n_half; x++) { tmp_data[y*dst_w + x].weight_sum += origin_tune; tmp_data[y*dst_w + x].pixel_sum += origin_tune * src[y*bw + x]; } } continue; } // Build integral functions->build_integral(integral, integral_stride, src, src_pre, compare, compare_pre, w, border, dst_w, dst_h, dx, dy); // Average displacement // TODO: Parallelize this for (int y = 0; y <= dst_h-n; y++) { const uint32_t *integral_ptr1 = integral + (y -1)*integral_stride - 1; const uint32_t *integral_ptr2 = integral + (y+n-1)*integral_stride - 1; for (int x = 0; x <= dst_w-n; x++) { const int xc = x + n_half; const int yc = y + n_half; // Difference between patches const int diff = (uint32_t)(integral_ptr2[n] - integral_ptr2[0] - integral_ptr1[n] + integral_ptr1[0]); // Sum pixel with weight if (diff < diff_max) { const int diffidx = diff * weight_fact_table; //float weight = exp(-diff*weightFact); const float weight = exptable[diffidx]; tmp_data[yc*dst_w + xc].weight_sum += weight; tmp_data[yc*dst_w + xc].pixel_sum += weight * compare[(yc+dy)*bw + xc + dx]; } integral_ptr1++; integral_ptr2++; } } } } } // Copy edges for (int y = 0; y < dst_h; y++) { for (int x = 0; x < n_half; x++) { *(dst + y * dst_s + x) = *(src + y * bw - x - 1); *(dst + y * dst_s - x + (dst_w - 1)) = *(src + y * bw + x + dst_w); } } for (int y = 0; y < n_half; y++) { memcpy(dst + y*dst_s, src - (y+1)*bw, dst_w); memcpy(dst + (dst_h-y-1)*dst_s, src + (y+dst_h)*bw, dst_w); } // Copy main image uint8_t result; for (int y = n_half; y < dst_h-n_half; y++) { for (int x = n_half; x < dst_w-n_half; x++) { result = (uint8_t)(tmp_data[y*dst_w + x].pixel_sum / tmp_data[y*dst_w + x].weight_sum); *(dst + y*dst_s + x) = result ? result : *(src + y*bw + x); } } free(tmp_data); free(integral_mem); } static int nlmeans_init(hb_filter_object_t *filter, hb_filter_init_t *init) { filter->private_data = calloc(sizeof(struct hb_filter_private_s), 1); hb_filter_private_t *pv = filter->private_data; NLMeansFunctions *functions = &pv->functions; functions->build_integral = build_integral_scalar; #if defined(ARCH_X86) nlmeans_init_x86(functions); #endif // Mark parameters unset for (int c = 0; c < 3; c++) { pv->strength[c] = -1; pv->origin_tune[c] = -1; pv->patch_size[c] = -1; pv->range[c] = -1; pv->nframes[c] = -1; pv->prefilter[c] = -1; } // Read user parameters if (filter->settings != NULL) { hb_dict_t * dict = filter->settings; hb_dict_extract_double(&pv->strength[0], dict, "y-strength"); hb_dict_extract_double(&pv->origin_tune[0], dict, "y-origin-tune"); hb_dict_extract_int(&pv->patch_size[0], dict, "y-patch-size"); hb_dict_extract_int(&pv->range[0], dict, "y-range"); hb_dict_extract_int(&pv->nframes[0], dict, "y-frame-count"); hb_dict_extract_int(&pv->prefilter[0], dict, "y-prefilter"); hb_dict_extract_double(&pv->strength[1], dict, "cb-strength"); hb_dict_extract_double(&pv->origin_tune[1], dict, "cb-origin-tune"); hb_dict_extract_int(&pv->patch_size[1], dict, "cb-patch-size"); hb_dict_extract_int(&pv->range[1], dict, "cb-range"); hb_dict_extract_int(&pv->nframes[1], dict, "cb-frame-count"); hb_dict_extract_int(&pv->prefilter[1], dict, "cb-prefilter"); hb_dict_extract_double(&pv->strength[2], dict, "cr-strength"); hb_dict_extract_double(&pv->origin_tune[2], dict, "cr-origin-tune"); hb_dict_extract_int(&pv->patch_size[2], dict, "cr-patch-size"); hb_dict_extract_int(&pv->range[2], dict, "cr-range"); hb_dict_extract_int(&pv->nframes[2], dict, "cr-frame-count"); hb_dict_extract_int(&pv->prefilter[2], dict, "cr-prefilter"); } // Cascade values // Cr not set; inherit Cb. Cb not set; inherit Y. Y not set; defaults. for (int c = 1; c < 3; c++) { if (pv->strength[c] == -1) { pv->strength[c] = pv->strength[c-1]; } if (pv->origin_tune[c] == -1) { pv->origin_tune[c] = pv->origin_tune[c-1]; } if (pv->patch_size[c] == -1) { pv->patch_size[c] = pv->patch_size[c-1]; } if (pv->range[c] == -1) { pv->range[c] = pv->range[c-1]; } if (pv->nframes[c] == -1) { pv->nframes[c] = pv->nframes[c-1]; } if (pv->prefilter[c] == -1) { pv->prefilter[c] = pv->prefilter[c-1]; } } for (int c = 0; c < 3; c++) { // Replace unset values with defaults if (pv->strength[c] == -1) { pv->strength[c] = c ? NLMEANS_STRENGTH_LUMA_DEFAULT : NLMEANS_STRENGTH_CHROMA_DEFAULT; } if (pv->origin_tune[c] == -1) { pv->origin_tune[c] = c ? NLMEANS_ORIGIN_TUNE_LUMA_DEFAULT : NLMEANS_ORIGIN_TUNE_CHROMA_DEFAULT; } if (pv->patch_size[c] == -1) { pv->patch_size[c] = c ? NLMEANS_PATCH_SIZE_LUMA_DEFAULT : NLMEANS_PATCH_SIZE_CHROMA_DEFAULT; } if (pv->range[c] == -1) { pv->range[c] = c ? NLMEANS_RANGE_LUMA_DEFAULT : NLMEANS_RANGE_CHROMA_DEFAULT; } if (pv->nframes[c] == -1) { pv->nframes[c] = c ? NLMEANS_FRAMES_LUMA_DEFAULT : NLMEANS_FRAMES_CHROMA_DEFAULT; } if (pv->prefilter[c] == -1) { pv->prefilter[c] = c ? NLMEANS_PREFILTER_LUMA_DEFAULT : NLMEANS_PREFILTER_CHROMA_DEFAULT; } // Sanitize if (pv->strength[c] < 0) { pv->strength[c] = 0; } if (pv->origin_tune[c] < 0.01) { pv->origin_tune[c] = 0.01; } // avoid black artifacts if (pv->origin_tune[c] > 1) { pv->origin_tune[c] = 1; } if (pv->patch_size[c] % 2 == 0) { pv->patch_size[c]--; } if (pv->patch_size[c] < 1) { pv->patch_size[c] = 1; } if (pv->range[c] % 2 == 0) { pv->range[c]--; } if (pv->range[c] < 1) { pv->range[c] = 1; } if (pv->nframes[c] < 1) { pv->nframes[c] = 1; } if (pv->nframes[c] > NLMEANS_FRAMES_MAX) { pv->nframes[c] = NLMEANS_FRAMES_MAX; } if (pv->prefilter[c] < 0) { pv->prefilter[c] = 0; } if (pv->max_frames < pv->nframes[c]) pv->max_frames = pv->nframes[c]; // Precompute exponential table float *exptable = &pv->exptable[c][0]; float *weight_fact_table = &pv->weight_fact_table[c]; int *diff_max = &pv->diff_max[c]; const float weight_factor = 1.0/pv->patch_size[c]/pv->patch_size[c] / (pv->strength[c] * pv->strength[c]); const float min_weight_in_table = 0.0005; const float stretch = NLMEANS_EXPSIZE / (-log(min_weight_in_table)); *(weight_fact_table) = weight_factor * stretch; *(diff_max) = NLMEANS_EXPSIZE / *(weight_fact_table); for (int i = 0; i < NLMEANS_EXPSIZE; i++) { exptable[i] = exp(-i/stretch); } exptable[NLMEANS_EXPSIZE-1] = 0; } pv->thread_count = hb_get_cpu_count(); pv->frame = calloc(pv->thread_count + pv->max_frames, sizeof(Frame)); for (int ii = 0; ii < pv->thread_count + pv->max_frames; ii++) { for (int c = 0; c < 3; c++) { pv->frame[ii].plane[c].mutex = hb_lock_init(); } } pv->thread_data = malloc(pv->thread_count * sizeof(nlmeans_thread_arg_t*)); if (taskset_init(&pv->taskset, pv->thread_count, sizeof(nlmeans_thread_arg_t)) == 0) { hb_error("NLMeans could not initialize taskset"); goto fail; } for (int ii = 0; ii < pv->thread_count; ii++) { pv->thread_data[ii] = taskset_thread_args(&pv->taskset, ii); if (pv->thread_data[ii] == NULL) { hb_error("NLMeans could not create thread args"); goto fail; } pv->thread_data[ii]->pv = pv; pv->thread_data[ii]->segment = ii; if (taskset_thread_spawn(&pv->taskset, ii, "nlmeans_filter", nlmeans_filter_thread, HB_NORMAL_PRIORITY) == 0) { hb_error("NLMeans could not spawn thread"); goto fail; } } return 0; fail: taskset_fini(&pv->taskset); free(pv->thread_data); free(pv); return -1; } static void nlmeans_close(hb_filter_object_t *filter) { hb_filter_private_t *pv = filter->private_data; if (pv == NULL) { return; } taskset_fini(&pv->taskset); for (int c = 0; c < 3; c++) { for (int f = 0; f < pv->nframes[c]; f++) { if (pv->frame[f].plane[c].mem_pre != NULL && pv->frame[f].plane[c].mem_pre != pv->frame[f].plane[c].mem) { free(pv->frame[f].plane[c].mem_pre); pv->frame[f].plane[c].mem_pre = NULL; } if (pv->frame[f].plane[c].mem != NULL) { free(pv->frame[f].plane[c].mem); pv->frame[f].plane[c].mem = NULL; } } } for (int ii = 0; ii < pv->thread_count + pv->max_frames; ii++) { for (int c = 0; c < 3; c++) { hb_lock_close(&pv->frame[ii].plane[c].mutex); } } free(pv->frame); free(pv->thread_data); free(pv); filter->private_data = NULL; } static void nlmeans_filter_thread(void *thread_args_v) { nlmeans_thread_arg_t *thread_data = thread_args_v; hb_filter_private_t *pv = thread_data->pv; int segment = thread_data->segment; hb_log("NLMeans thread started for segment %d", segment); while (1) { // Wait until there is work to do. taskset_thread_wait4start(&pv->taskset, segment); if (taskset_thread_stop(&pv->taskset, segment)) { break; } Frame *frame = &pv->frame[segment]; hb_buffer_t *buf; buf = hb_frame_buffer_init(frame->fmt, frame->width, frame->height); NLMeansFunctions *functions = &pv->functions; for (int c = 0; c < 3; c++) { if (pv->strength[c] == 0) { nlmeans_deborder(&frame->plane[c], buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height); continue; } if (pv->prefilter[c] & NLMEANS_PREFILTER_MODE_PASSTHRU) { nlmeans_prefilter(&pv->frame->plane[c], pv->prefilter[c]); nlmeans_deborder(&frame->plane[c], buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height); continue; } // Process current plane nlmeans_plane(functions, frame, pv->prefilter[c], c, pv->nframes[c], buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height, pv->strength[c], pv->origin_tune[c], pv->patch_size[c], pv->range[c], pv->exptable[c], pv->weight_fact_table[c], pv->diff_max[c]); } buf->s = pv->frame[segment].s; thread_data->out = buf; // Finished this segment, notify. taskset_thread_complete(&pv->taskset, segment); } taskset_thread_complete(&pv->taskset, segment); } static void nlmeans_add_frame(hb_filter_private_t *pv, hb_buffer_t *buf) { for (int c = 0; c < 3; c++) { // Extend copy of plane with extra border and place in buffer const int border = ((pv->range[c] + 2) / 2 + 15) / 16 * 16; nlmeans_alloc(buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height, &pv->frame[pv->next_frame].plane[c], border); pv->frame[pv->next_frame].s = buf->s; pv->frame[pv->next_frame].width = buf->f.width; pv->frame[pv->next_frame].height = buf->f.height; pv->frame[pv->next_frame].fmt = buf->f.fmt; } pv->next_frame++; } static hb_buffer_t * nlmeans_filter(hb_filter_private_t *pv) { if (pv->next_frame < pv->max_frames + pv->thread_count) { return NULL; } taskset_cycle(&pv->taskset); // Free buffers that are not needed for next taskset cycle for (int c = 0; c < 3; c++) { for (int t = 0; t < pv->thread_count; t++) { // Release last frame in buffer if (pv->frame[t].plane[c].mem_pre != NULL && pv->frame[t].plane[c].mem_pre != pv->frame[t].plane[c].mem) { free(pv->frame[t].plane[c].mem_pre); pv->frame[t].plane[c].mem_pre = NULL; } if (pv->frame[t].plane[c].mem != NULL) { free(pv->frame[t].plane[c].mem); pv->frame[t].plane[c].mem = NULL; } } } // Shift frames in buffer down for (int f = 0; f < pv->max_frames; f++) { // Don't move the mutex! Frame frame = pv->frame[f]; pv->frame[f] = pv->frame[f+pv->thread_count]; for (int c = 0; c < 3; c++) { pv->frame[f].plane[c].mutex = frame.plane[c].mutex; pv->frame[f+pv->thread_count].plane[c].mem_pre = NULL; pv->frame[f+pv->thread_count].plane[c].mem = NULL; } } pv->next_frame -= pv->thread_count; // Collect results from taskset hb_buffer_list_t list; hb_buffer_list_clear(&list); for (int t = 0; t < pv->thread_count; t++) { hb_buffer_list_append(&list, pv->thread_data[t]->out); } return hb_buffer_list_clear(&list); } static hb_buffer_t * nlmeans_filter_flush(hb_filter_private_t *pv) { hb_buffer_list_t list; hb_buffer_list_clear(&list); for (int f = 0; f < pv->next_frame; f++) { Frame *frame = &pv->frame[f]; hb_buffer_t *buf; buf = hb_frame_buffer_init(frame->fmt, frame->width, frame->height); NLMeansFunctions *functions = &pv->functions; for (int c = 0; c < 3; c++) { if (pv->strength[c] == 0) { nlmeans_deborder(&frame->plane[c], buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height); continue; } if (pv->prefilter[c] & NLMEANS_PREFILTER_MODE_PASSTHRU) { nlmeans_prefilter(&pv->frame[f].plane[c], pv->prefilter[c]); nlmeans_deborder(&frame->plane[c], buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height); continue; } int nframes = pv->next_frame - f; if (pv->nframes[c] < nframes) { nframes = pv->nframes[c]; } // Process current plane nlmeans_plane(functions, frame, pv->prefilter[c], c, nframes, buf->plane[c].data, buf->plane[c].width, buf->plane[c].stride, buf->plane[c].height, pv->strength[c], pv->origin_tune[c], pv->patch_size[c], pv->range[c], pv->exptable[c], pv->weight_fact_table[c], pv->diff_max[c]); } buf->s = frame->s; hb_buffer_list_append(&list, buf); } return hb_buffer_list_clear(&list); } static int nlmeans_work(hb_filter_object_t *filter, hb_buffer_t **buf_in, hb_buffer_t **buf_out ) { hb_filter_private_t *pv = filter->private_data; hb_buffer_t *in = *buf_in; if (in->s.flags & HB_BUF_FLAG_EOF) { hb_buffer_list_t list; hb_buffer_t *buf; // Flush buffered frames buf = nlmeans_filter_flush(pv); hb_buffer_list_set(&list, buf); // And terminate the buffer list with a EOF buffer hb_buffer_list_append(&list, in); *buf_out = hb_buffer_list_clear(&list); *buf_in = NULL; return HB_FILTER_DONE; } nlmeans_add_frame(pv, in); *buf_out = nlmeans_filter(pv); return HB_FILTER_OK; }