Index: source/libvpx/vp9/encoder/vp9_ssim.c |
diff --git a/source/libvpx/vp9/encoder/vp9_ssim.c b/source/libvpx/vp9/encoder/vp9_ssim.c |
deleted file mode 100644 |
index 172de5d1daa6ce66a66581149a2b49bc3f6b4666..0000000000000000000000000000000000000000 |
--- a/source/libvpx/vp9/encoder/vp9_ssim.c |
+++ /dev/null |
@@ -1,500 +0,0 @@ |
-/* |
- * Copyright (c) 2010 The WebM project authors. All Rights Reserved. |
- * |
- * Use of this source code is governed by a BSD-style license |
- * that can be found in the LICENSE file in the root of the source |
- * tree. An additional intellectual property rights grant can be found |
- * in the file PATENTS. All contributing project authors may |
- * be found in the AUTHORS file in the root of the source tree. |
- */ |
- |
-#include <math.h> |
-#include "./vp9_rtcd.h" |
-#include "vpx_ports/mem.h" |
-#include "vp9/encoder/vp9_ssim.h" |
- |
-void vp9_ssim_parms_16x16_c(uint8_t *s, int sp, uint8_t *r, |
- int rp, unsigned long *sum_s, unsigned long *sum_r, |
- unsigned long *sum_sq_s, unsigned long *sum_sq_r, |
- unsigned long *sum_sxr) { |
- int i, j; |
- for (i = 0; i < 16; i++, s += sp, r += rp) { |
- for (j = 0; j < 16; j++) { |
- *sum_s += s[j]; |
- *sum_r += r[j]; |
- *sum_sq_s += s[j] * s[j]; |
- *sum_sq_r += r[j] * r[j]; |
- *sum_sxr += s[j] * r[j]; |
- } |
- } |
-} |
-void vp9_ssim_parms_8x8_c(uint8_t *s, int sp, uint8_t *r, int rp, |
- unsigned long *sum_s, unsigned long *sum_r, |
- unsigned long *sum_sq_s, unsigned long *sum_sq_r, |
- unsigned long *sum_sxr) { |
- int i, j; |
- for (i = 0; i < 8; i++, s += sp, r += rp) { |
- for (j = 0; j < 8; j++) { |
- *sum_s += s[j]; |
- *sum_r += r[j]; |
- *sum_sq_s += s[j] * s[j]; |
- *sum_sq_r += r[j] * r[j]; |
- *sum_sxr += s[j] * r[j]; |
- } |
- } |
-} |
- |
-#if CONFIG_VP9_HIGHBITDEPTH |
-void vp9_highbd_ssim_parms_8x8_c(uint16_t *s, int sp, uint16_t *r, int rp, |
- uint32_t *sum_s, uint32_t *sum_r, |
- uint32_t *sum_sq_s, uint32_t *sum_sq_r, |
- uint32_t *sum_sxr) { |
- int i, j; |
- for (i = 0; i < 8; i++, s += sp, r += rp) { |
- for (j = 0; j < 8; j++) { |
- *sum_s += s[j]; |
- *sum_r += r[j]; |
- *sum_sq_s += s[j] * s[j]; |
- *sum_sq_r += r[j] * r[j]; |
- *sum_sxr += s[j] * r[j]; |
- } |
- } |
-} |
-#endif // CONFIG_VP9_HIGHBITDEPTH |
- |
-static const int64_t cc1 = 26634; // (64^2*(.01*255)^2 |
-static const int64_t cc2 = 239708; // (64^2*(.03*255)^2 |
- |
-static double similarity(unsigned long sum_s, unsigned long sum_r, |
- unsigned long sum_sq_s, unsigned long sum_sq_r, |
- unsigned long sum_sxr, int count) { |
- int64_t ssim_n, ssim_d; |
- int64_t c1, c2; |
- |
- // scale the constants by number of pixels |
- c1 = (cc1 * count * count) >> 12; |
- c2 = (cc2 * count * count) >> 12; |
- |
- ssim_n = (2 * sum_s * sum_r + c1) * ((int64_t) 2 * count * sum_sxr - |
- (int64_t) 2 * sum_s * sum_r + c2); |
- |
- ssim_d = (sum_s * sum_s + sum_r * sum_r + c1) * |
- ((int64_t)count * sum_sq_s - (int64_t)sum_s * sum_s + |
- (int64_t)count * sum_sq_r - (int64_t) sum_r * sum_r + c2); |
- |
- return ssim_n * 1.0 / ssim_d; |
-} |
- |
-static double ssim_8x8(uint8_t *s, int sp, uint8_t *r, int rp) { |
- unsigned long sum_s = 0, sum_r = 0, sum_sq_s = 0, sum_sq_r = 0, sum_sxr = 0; |
- vp9_ssim_parms_8x8(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, |
- &sum_sxr); |
- return similarity(sum_s, sum_r, sum_sq_s, sum_sq_r, sum_sxr, 64); |
-} |
- |
-#if CONFIG_VP9_HIGHBITDEPTH |
-static double highbd_ssim_8x8(uint16_t *s, int sp, uint16_t *r, int rp, |
- unsigned int bd) { |
- uint32_t sum_s = 0, sum_r = 0, sum_sq_s = 0, sum_sq_r = 0, sum_sxr = 0; |
- const int oshift = bd - 8; |
- vp9_highbd_ssim_parms_8x8(s, sp, r, rp, &sum_s, &sum_r, &sum_sq_s, &sum_sq_r, |
- &sum_sxr); |
- return similarity(sum_s >> oshift, |
- sum_r >> oshift, |
- sum_sq_s >> (2 * oshift), |
- sum_sq_r >> (2 * oshift), |
- sum_sxr >> (2 * oshift), |
- 64); |
-} |
-#endif // CONFIG_VP9_HIGHBITDEPTH |
- |
-// We are using a 8x8 moving window with starting location of each 8x8 window |
-// on the 4x4 pixel grid. Such arrangement allows the windows to overlap |
-// block boundaries to penalize blocking artifacts. |
-double vp9_ssim2(uint8_t *img1, uint8_t *img2, int stride_img1, |
- int stride_img2, int width, int height) { |
- int i, j; |
- int samples = 0; |
- double ssim_total = 0; |
- |
- // sample point start with each 4x4 location |
- for (i = 0; i <= height - 8; |
- i += 4, img1 += stride_img1 * 4, img2 += stride_img2 * 4) { |
- for (j = 0; j <= width - 8; j += 4) { |
- double v = ssim_8x8(img1 + j, stride_img1, img2 + j, stride_img2); |
- ssim_total += v; |
- samples++; |
- } |
- } |
- ssim_total /= samples; |
- return ssim_total; |
-} |
- |
-#if CONFIG_VP9_HIGHBITDEPTH |
-double vp9_highbd_ssim2(uint8_t *img1, uint8_t *img2, int stride_img1, |
- int stride_img2, int width, int height, |
- unsigned int bd) { |
- int i, j; |
- int samples = 0; |
- double ssim_total = 0; |
- |
- // sample point start with each 4x4 location |
- for (i = 0; i <= height - 8; |
- i += 4, img1 += stride_img1 * 4, img2 += stride_img2 * 4) { |
- for (j = 0; j <= width - 8; j += 4) { |
- double v = highbd_ssim_8x8(CONVERT_TO_SHORTPTR(img1 + j), stride_img1, |
- CONVERT_TO_SHORTPTR(img2 + j), stride_img2, |
- bd); |
- ssim_total += v; |
- samples++; |
- } |
- } |
- ssim_total /= samples; |
- return ssim_total; |
-} |
-#endif // CONFIG_VP9_HIGHBITDEPTH |
- |
-double vp9_calc_ssim(YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest, |
- double *weight) { |
- double a, b, c; |
- double ssimv; |
- |
- a = vp9_ssim2(source->y_buffer, dest->y_buffer, |
- source->y_stride, dest->y_stride, |
- source->y_crop_width, source->y_crop_height); |
- |
- b = vp9_ssim2(source->u_buffer, dest->u_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height); |
- |
- c = vp9_ssim2(source->v_buffer, dest->v_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height); |
- |
- ssimv = a * .8 + .1 * (b + c); |
- |
- *weight = 1; |
- |
- return ssimv; |
-} |
- |
-double vp9_calc_ssimg(YV12_BUFFER_CONFIG *source, YV12_BUFFER_CONFIG *dest, |
- double *ssim_y, double *ssim_u, double *ssim_v) { |
- double ssim_all = 0; |
- double a, b, c; |
- |
- a = vp9_ssim2(source->y_buffer, dest->y_buffer, |
- source->y_stride, dest->y_stride, |
- source->y_crop_width, source->y_crop_height); |
- |
- b = vp9_ssim2(source->u_buffer, dest->u_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height); |
- |
- c = vp9_ssim2(source->v_buffer, dest->v_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height); |
- *ssim_y = a; |
- *ssim_u = b; |
- *ssim_v = c; |
- ssim_all = (a * 4 + b + c) / 6; |
- |
- return ssim_all; |
-} |
- |
-// traditional ssim as per: http://en.wikipedia.org/wiki/Structural_similarity |
-// |
-// Re working out the math -> |
-// |
-// ssim(x,y) = (2*mean(x)*mean(y) + c1)*(2*cov(x,y)+c2) / |
-// ((mean(x)^2+mean(y)^2+c1)*(var(x)+var(y)+c2)) |
-// |
-// mean(x) = sum(x) / n |
-// |
-// cov(x,y) = (n*sum(xi*yi)-sum(x)*sum(y))/(n*n) |
-// |
-// var(x) = (n*sum(xi*xi)-sum(xi)*sum(xi))/(n*n) |
-// |
-// ssim(x,y) = |
-// (2*sum(x)*sum(y)/(n*n) + c1)*(2*(n*sum(xi*yi)-sum(x)*sum(y))/(n*n)+c2) / |
-// (((sum(x)*sum(x)+sum(y)*sum(y))/(n*n) +c1) * |
-// ((n*sum(xi*xi) - sum(xi)*sum(xi))/(n*n)+ |
-// (n*sum(yi*yi) - sum(yi)*sum(yi))/(n*n)+c2))) |
-// |
-// factoring out n*n |
-// |
-// ssim(x,y) = |
-// (2*sum(x)*sum(y) + n*n*c1)*(2*(n*sum(xi*yi)-sum(x)*sum(y))+n*n*c2) / |
-// (((sum(x)*sum(x)+sum(y)*sum(y)) + n*n*c1) * |
-// (n*sum(xi*xi)-sum(xi)*sum(xi)+n*sum(yi*yi)-sum(yi)*sum(yi)+n*n*c2)) |
-// |
-// Replace c1 with n*n * c1 for the final step that leads to this code: |
-// The final step scales by 12 bits so we don't lose precision in the constants. |
- |
-double ssimv_similarity(Ssimv *sv, int64_t n) { |
- // Scale the constants by number of pixels. |
- const int64_t c1 = (cc1 * n * n) >> 12; |
- const int64_t c2 = (cc2 * n * n) >> 12; |
- |
- const double l = 1.0 * (2 * sv->sum_s * sv->sum_r + c1) / |
- (sv->sum_s * sv->sum_s + sv->sum_r * sv->sum_r + c1); |
- |
- // Since these variables are unsigned sums, convert to double so |
- // math is done in double arithmetic. |
- const double v = (2.0 * n * sv->sum_sxr - 2 * sv->sum_s * sv->sum_r + c2) |
- / (n * sv->sum_sq_s - sv->sum_s * sv->sum_s + n * sv->sum_sq_r |
- - sv->sum_r * sv->sum_r + c2); |
- |
- return l * v; |
-} |
- |
-// The first term of the ssim metric is a luminance factor. |
-// |
-// (2*mean(x)*mean(y) + c1)/ (mean(x)^2+mean(y)^2+c1) |
-// |
-// This luminance factor is super sensitive to the dark side of luminance |
-// values and completely insensitive on the white side. check out 2 sets |
-// (1,3) and (250,252) the term gives ( 2*1*3/(1+9) = .60 |
-// 2*250*252/ (250^2+252^2) => .99999997 |
-// |
-// As a result in this tweaked version of the calculation in which the |
-// luminance is taken as percentage off from peak possible. |
-// |
-// 255 * 255 - (sum_s - sum_r) / count * (sum_s - sum_r) / count |
-// |
-double ssimv_similarity2(Ssimv *sv, int64_t n) { |
- // Scale the constants by number of pixels. |
- const int64_t c1 = (cc1 * n * n) >> 12; |
- const int64_t c2 = (cc2 * n * n) >> 12; |
- |
- const double mean_diff = (1.0 * sv->sum_s - sv->sum_r) / n; |
- const double l = (255 * 255 - mean_diff * mean_diff + c1) / (255 * 255 + c1); |
- |
- // Since these variables are unsigned, sums convert to double so |
- // math is done in double arithmetic. |
- const double v = (2.0 * n * sv->sum_sxr - 2 * sv->sum_s * sv->sum_r + c2) |
- / (n * sv->sum_sq_s - sv->sum_s * sv->sum_s + |
- n * sv->sum_sq_r - sv->sum_r * sv->sum_r + c2); |
- |
- return l * v; |
-} |
-void ssimv_parms(uint8_t *img1, int img1_pitch, uint8_t *img2, int img2_pitch, |
- Ssimv *sv) { |
- vp9_ssim_parms_8x8(img1, img1_pitch, img2, img2_pitch, |
- &sv->sum_s, &sv->sum_r, &sv->sum_sq_s, &sv->sum_sq_r, |
- &sv->sum_sxr); |
-} |
- |
-double vp9_get_ssim_metrics(uint8_t *img1, int img1_pitch, |
- uint8_t *img2, int img2_pitch, |
- int width, int height, |
- Ssimv *sv2, Metrics *m, |
- int do_inconsistency) { |
- double dssim_total = 0; |
- double ssim_total = 0; |
- double ssim2_total = 0; |
- double inconsistency_total = 0; |
- int i, j; |
- int c = 0; |
- double norm; |
- double old_ssim_total = 0; |
- vp9_clear_system_state(); |
- // We can sample points as frequently as we like start with 1 per 4x4. |
- for (i = 0; i < height; i += 4, |
- img1 += img1_pitch * 4, img2 += img2_pitch * 4) { |
- for (j = 0; j < width; j += 4, ++c) { |
- Ssimv sv = {0}; |
- double ssim; |
- double ssim2; |
- double dssim; |
- uint32_t var_new; |
- uint32_t var_old; |
- uint32_t mean_new; |
- uint32_t mean_old; |
- double ssim_new; |
- double ssim_old; |
- |
- // Not sure there's a great way to handle the edge pixels |
- // in ssim when using a window. Seems biased against edge pixels |
- // however you handle this. This uses only samples that are |
- // fully in the frame. |
- if (j + 8 <= width && i + 8 <= height) { |
- ssimv_parms(img1 + j, img1_pitch, img2 + j, img2_pitch, &sv); |
- } |
- |
- ssim = ssimv_similarity(&sv, 64); |
- ssim2 = ssimv_similarity2(&sv, 64); |
- |
- sv.ssim = ssim2; |
- |
- // dssim is calculated to use as an actual error metric and |
- // is scaled up to the same range as sum square error. |
- // Since we are subsampling every 16th point maybe this should be |
- // *16 ? |
- dssim = 255 * 255 * (1 - ssim2) / 2; |
- |
- // Here I introduce a new error metric: consistency-weighted |
- // SSIM-inconsistency. This metric isolates frames where the |
- // SSIM 'suddenly' changes, e.g. if one frame in every 8 is much |
- // sharper or blurrier than the others. Higher values indicate a |
- // temporally inconsistent SSIM. There are two ideas at work: |
- // |
- // 1) 'SSIM-inconsistency': the total inconsistency value |
- // reflects how much SSIM values are changing between this |
- // source / reference frame pair and the previous pair. |
- // |
- // 2) 'consistency-weighted': weights de-emphasize areas in the |
- // frame where the scene content has changed. Changes in scene |
- // content are detected via changes in local variance and local |
- // mean. |
- // |
- // Thus the overall measure reflects how inconsistent the SSIM |
- // values are, over consistent regions of the frame. |
- // |
- // The metric has three terms: |
- // |
- // term 1 -> uses change in scene Variance to weight error score |
- // 2 * var(Fi)*var(Fi-1) / (var(Fi)^2+var(Fi-1)^2) |
- // larger changes from one frame to the next mean we care |
- // less about consistency. |
- // |
- // term 2 -> uses change in local scene luminance to weight error |
- // 2 * avg(Fi)*avg(Fi-1) / (avg(Fi)^2+avg(Fi-1)^2) |
- // larger changes from one frame to the next mean we care |
- // less about consistency. |
- // |
- // term3 -> measures inconsistency in ssim scores between frames |
- // 1 - ( 2 * ssim(Fi)*ssim(Fi-1)/(ssim(Fi)^2+sssim(Fi-1)^2). |
- // |
- // This term compares the ssim score for the same location in 2 |
- // subsequent frames. |
- var_new = sv.sum_sq_s - sv.sum_s * sv.sum_s / 64; |
- var_old = sv2[c].sum_sq_s - sv2[c].sum_s * sv2[c].sum_s / 64; |
- mean_new = sv.sum_s; |
- mean_old = sv2[c].sum_s; |
- ssim_new = sv.ssim; |
- ssim_old = sv2[c].ssim; |
- |
- if (do_inconsistency) { |
- // We do the metric once for every 4x4 block in the image. Since |
- // we are scaling the error to SSE for use in a psnr calculation |
- // 1.0 = 4x4x255x255 the worst error we can possibly have. |
- static const double kScaling = 4. * 4 * 255 * 255; |
- |
- // The constants have to be non 0 to avoid potential divide by 0 |
- // issues other than that they affect kind of a weighting between |
- // the terms. No testing of what the right terms should be has been |
- // done. |
- static const double c1 = 1, c2 = 1, c3 = 1; |
- |
- // This measures how much consistent variance is in two consecutive |
- // source frames. 1.0 means they have exactly the same variance. |
- const double variance_term = (2.0 * var_old * var_new + c1) / |
- (1.0 * var_old * var_old + 1.0 * var_new * var_new + c1); |
- |
- // This measures how consistent the local mean are between two |
- // consecutive frames. 1.0 means they have exactly the same mean. |
- const double mean_term = (2.0 * mean_old * mean_new + c2) / |
- (1.0 * mean_old * mean_old + 1.0 * mean_new * mean_new + c2); |
- |
- // This measures how consistent the ssims of two |
- // consecutive frames is. 1.0 means they are exactly the same. |
- double ssim_term = pow((2.0 * ssim_old * ssim_new + c3) / |
- (ssim_old * ssim_old + ssim_new * ssim_new + c3), |
- 5); |
- |
- double this_inconsistency; |
- |
- // Floating point math sometimes makes this > 1 by a tiny bit. |
- // We want the metric to scale between 0 and 1.0 so we can convert |
- // it to an snr scaled value. |
- if (ssim_term > 1) |
- ssim_term = 1; |
- |
- // This converts the consistency metric to an inconsistency metric |
- // ( so we can scale it like psnr to something like sum square error. |
- // The reason for the variance and mean terms is the assumption that |
- // if there are big changes in the source we shouldn't penalize |
- // inconsistency in ssim scores a bit less as it will be less visible |
- // to the user. |
- this_inconsistency = (1 - ssim_term) * variance_term * mean_term; |
- |
- this_inconsistency *= kScaling; |
- inconsistency_total += this_inconsistency; |
- } |
- sv2[c] = sv; |
- ssim_total += ssim; |
- ssim2_total += ssim2; |
- dssim_total += dssim; |
- |
- old_ssim_total += ssim_old; |
- } |
- old_ssim_total += 0; |
- } |
- |
- norm = 1. / (width / 4) / (height / 4); |
- ssim_total *= norm; |
- ssim2_total *= norm; |
- m->ssim2 = ssim2_total; |
- m->ssim = ssim_total; |
- if (old_ssim_total == 0) |
- inconsistency_total = 0; |
- |
- m->ssimc = inconsistency_total; |
- |
- m->dssim = dssim_total; |
- return inconsistency_total; |
-} |
- |
- |
-#if CONFIG_VP9_HIGHBITDEPTH |
-double vp9_highbd_calc_ssim(YV12_BUFFER_CONFIG *source, |
- YV12_BUFFER_CONFIG *dest, |
- double *weight, unsigned int bd) { |
- double a, b, c; |
- double ssimv; |
- |
- a = vp9_highbd_ssim2(source->y_buffer, dest->y_buffer, |
- source->y_stride, dest->y_stride, |
- source->y_crop_width, source->y_crop_height, bd); |
- |
- b = vp9_highbd_ssim2(source->u_buffer, dest->u_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height, bd); |
- |
- c = vp9_highbd_ssim2(source->v_buffer, dest->v_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height, bd); |
- |
- ssimv = a * .8 + .1 * (b + c); |
- |
- *weight = 1; |
- |
- return ssimv; |
-} |
- |
-double vp9_highbd_calc_ssimg(YV12_BUFFER_CONFIG *source, |
- YV12_BUFFER_CONFIG *dest, double *ssim_y, |
- double *ssim_u, double *ssim_v, unsigned int bd) { |
- double ssim_all = 0; |
- double a, b, c; |
- |
- a = vp9_highbd_ssim2(source->y_buffer, dest->y_buffer, |
- source->y_stride, dest->y_stride, |
- source->y_crop_width, source->y_crop_height, bd); |
- |
- b = vp9_highbd_ssim2(source->u_buffer, dest->u_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height, bd); |
- |
- c = vp9_highbd_ssim2(source->v_buffer, dest->v_buffer, |
- source->uv_stride, dest->uv_stride, |
- source->uv_crop_width, source->uv_crop_height, bd); |
- *ssim_y = a; |
- *ssim_u = b; |
- *ssim_v = c; |
- ssim_all = (a * 4 + b + c) / 6; |
- |
- return ssim_all; |
-} |
-#endif // CONFIG_VP9_HIGHBITDEPTH |