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add LSIM metric to WebPPictureDistortion()

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LSIM stands for "local similarity": before matching
a compressed pixel to the source, we search around in the source
and minimise the squared error. So, this is close to PSNR calculation,
but mitigates some of its limitations (pure translation and noise for instance).

There's a new -print_lsim option to cwebp too.

Change-Id: Ia38561034c7a90e71d2ea0f55bb1de527eda245b
This commit is contained in:
Pascal Massimino
2012-10-18 08:26:40 -07:00
parent c3aa215afa
commit f86e6abe1f
5 changed files with 129 additions and 52 deletions
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144
src/enc/picture.c
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@ -906,67 +906,135 @@ void WebPCleanupTransparentArea(WebPPicture* pic) {
#undef SIZE
#undef SIZE2
//------------------------------------------------------------------------------
// local-min distortion
//
// For every pixel in the *reference* picture, we search for the local best
// match in the compressed image. This is not a symmetrical measure.
// search radius. Shouldn't be too large.
#define RADIUS 2
static double AccumulateLSIM(const uint8_t* src, int src_stride,
const uint8_t* ref, int ref_stride,
int w, int h) {
int x, y;
double total_sse = 0.;
for (y = 0; y < h; ++y) {
const int y0 = (y - RADIUS < 0) ? 0 : y - RADIUS;
const int y1 = (y + RADIUS + 1 >= h) ? h : y + RADIUS + 1;
for (x = 0; x < w; ++x) {
const int x0 = (x - RADIUS < 0) ? 0 : x - RADIUS;
const int x1 = (x + RADIUS + 1 >= w) ? w : x + RADIUS + 1;
double best_sse = 255. * 255.;
const double value = (double)ref[y * ref_stride + x];
int i, j;
for (j = y0; j < y1; ++j) {
const uint8_t* s = src + j * src_stride;
for (i = x0; i < x1; ++i) {
const double sse = (double)(s[i] - value) * (s[i] - value);
if (sse < best_sse) best_sse = sse;
}
}
total_sse += best_sse;
}
}
return total_sse;
}
#undef RADIUS
//------------------------------------------------------------------------------
// Distortion
// Max value returned in case of exact similarity.
static const double kMinDistortion_dB = 99.;
static float GetPSNR(const double v) {
return (float)((v > 0.) ? -4.3429448 * log(v / (255 * 255.))
: kMinDistortion_dB);
}
int WebPPictureDistortion(const WebPPicture* pic1, const WebPPicture* pic2,
int WebPPictureDistortion(const WebPPicture* src, const WebPPicture* ref,
int type, float result[5]) {
int c;
DistoStats stats[5];
int has_alpha;
int uv_w, uv_h;
if (pic1 == NULL || pic2 == NULL ||
pic1->width != pic2->width || pic1->height != pic2->height ||
pic1->y == NULL || pic2->y == NULL ||
pic1->u == NULL || pic2->u == NULL ||
pic1->v == NULL || pic2->v == NULL ||
if (src == NULL || ref == NULL ||
src->width != ref->width || src->height != ref->height ||
src->y == NULL || ref->y == NULL ||
src->u == NULL || ref->u == NULL ||
src->v == NULL || ref->v == NULL ||
result == NULL) {
return 0;
}
// TODO(skal): provide distortion for ARGB too.
if (pic1->use_argb == 1 || pic1->use_argb != pic2->use_argb) {
if (src->use_argb == 1 || src->use_argb != ref->use_argb) {
return 0;
}
has_alpha = !!(pic1->colorspace & WEBP_CSP_ALPHA_BIT);
if (has_alpha != !!(pic2->colorspace & WEBP_CSP_ALPHA_BIT) ||
(has_alpha && (pic1->a == NULL || pic2->a == NULL))) {
has_alpha = !!(src->colorspace & WEBP_CSP_ALPHA_BIT);
if (has_alpha != !!(ref->colorspace & WEBP_CSP_ALPHA_BIT) ||
(has_alpha && (src->a == NULL || ref->a == NULL))) {
return 0;
}
memset(stats, 0, sizeof(stats));
VP8SSIMAccumulatePlane(pic1->y, pic1->y_stride,
pic2->y, pic2->y_stride,
pic1->width, pic1->height, &stats[0]);
VP8SSIMAccumulatePlane(pic1->u, pic1->uv_stride,
pic2->u, pic2->uv_stride,
(pic1->width + 1) >> 1, (pic1->height + 1) >> 1,
&stats[1]);
VP8SSIMAccumulatePlane(pic1->v, pic1->uv_stride,
pic2->v, pic2->uv_stride,
(pic1->width + 1) >> 1, (pic1->height + 1) >> 1,
&stats[2]);
if (has_alpha) {
VP8SSIMAccumulatePlane(pic1->a, pic1->a_stride,
pic2->a, pic2->a_stride,
pic1->width, pic1->height, &stats[3]);
}
for (c = 0; c <= 4; ++c) {
if (type == 1) {
const double v = VP8SSIMGet(&stats[c]);
result[c] = (float)((v < 1.) ? -10.0 * log10(1. - v)
: kMinDistortion_dB);
} else {
const double v = VP8SSIMGetSquaredError(&stats[c]);
result[c] = (float)((v > 0.) ? -4.3429448 * log(v / (255 * 255.))
: kMinDistortion_dB);
uv_w = HALVE(src->width);
uv_h = HALVE(src->height);
if (type >= 2) {
float sse[4];
sse[0] = AccumulateLSIM(src->y, src->y_stride,
ref->y, ref->y_stride, src->width, src->height);
sse[1] = AccumulateLSIM(src->u, src->uv_stride,
ref->u, ref->uv_stride, uv_w, uv_h);
sse[2] = AccumulateLSIM(src->v, src->uv_stride,
ref->v, ref->uv_stride, uv_w, uv_h);
sse[3] = has_alpha ? AccumulateLSIM(src->a, src->a_stride,
ref->a, ref->a_stride,
src->width, src->height)
: 0;
result[0] = GetPSNR(sse[0] / (src->width * src->height));
result[1] = GetPSNR(sse[1] / (uv_w * uv_h));
result[2] = GetPSNR(sse[2] / (uv_w * uv_h));
result[3] = GetPSNR(sse[3] / (src->width * src->height));
{
double total_sse = sse[0] + sse[1] + sse[2];
int total_pixels = src->width * src->height + 2 * uv_w * uv_h;
if (has_alpha) {
total_pixels += src->width * src->height;
total_sse += sse[3];
}
result[4] = GetPSNR(total_sse / total_pixels);
}
} else {
int c;
VP8SSIMAccumulatePlane(src->y, src->y_stride,
ref->y, ref->y_stride,
src->width, src->height, &stats[0]);
VP8SSIMAccumulatePlane(src->u, src->uv_stride,
ref->u, ref->uv_stride,
uv_w, uv_h, &stats[1]);
VP8SSIMAccumulatePlane(src->v, src->uv_stride,
ref->v, ref->uv_stride,
uv_w, uv_h, &stats[2]);
if (has_alpha) {
VP8SSIMAccumulatePlane(src->a, src->a_stride,
ref->a, ref->a_stride,
src->width, src->height, &stats[3]);
}
for (c = 0; c <= 4; ++c) {
if (type == 1) {
const double v = VP8SSIMGet(&stats[c]);
result[c] = (float)((v < 1.) ? -10.0 * log10(1. - v)
: kMinDistortion_dB);
} else {
const double v = VP8SSIMGetSquaredError(&stats[c]);
result[c] = GetPSNR(v);
}
// Accumulate forward
if (c < 4) VP8SSIMAddStats(&stats[c], &stats[4]);
}
// Accumulate forward
if (c < 4) VP8SSIMAddStats(&stats[c], &stats[4]);
}
return 1;
}