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new segmentation algorithm

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fixes the 'blocky sky problem' (saturation problem: when luma was flat,
chroma noise was taking over, resulting in random segment id assigned.
When just using a common uniform segment was better).

+ side clean-up and readibility/experimentability MACRO'ization
+ added '-map 7' option

Change-Id: I35982a9e43c0fecbfdd7b05e4813e8ba8c121d71
This commit is contained in:
skal
2012-09-03 19:40:52 +02:00
parent 2cf1f81590
commit 5725cabac0
6 changed files with 135 additions and 95 deletions
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123
src/enc/analysis.c
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@ -23,10 +23,6 @@ extern "C" {
#define MAX_ITERS_K_MEANS 6
static int ClipAlpha(int alpha) {
return alpha < 0 ? 0 : alpha > 255 ? 255 : alpha;
}
//------------------------------------------------------------------------------
// Smooth the segment map by replacing isolated block by the majority of its
// neighbours.
@ -115,7 +111,7 @@ static void SetSegmentProbas(VP8Encoder* const enc) {
}
static WEBP_INLINE int clip(int v, int m, int M) {
return v < m ? m : v > M ? M : v;
return (v < m) ? m : (v > M) ? M : v;
}
static void SetSegmentAlphas(VP8Encoder* const enc,
@ -141,23 +137,64 @@ static void SetSegmentAlphas(VP8Encoder* const enc,
}
}
//------------------------------------------------------------------------------
// Compute susceptibility based on DCT-coeff histograms:
// the higher, the "easier" the macroblock is to compress.
#define MAX_ALPHA 255 // 8b of precision for susceptibilities.
#define ALPHA_SCALE (2 * MAX_ALPHA) // scaling factor for alpha.
#define DEFAULT_ALPHA (-1)
#define IS_BETTER_ALPHA(alpha, best_alpha) ((alpha) > (best_alpha))
static int FinalAlphaValue(int alpha) {
alpha = MAX_ALPHA - alpha;
return clip(alpha, 0, MAX_ALPHA);
}
static int GetAlpha(const VP8Histogram* const histo) {
int max_value = 0, last_non_zero = 1;
int k;
int alpha;
for (k = 0; k <= MAX_COEFF_THRESH; ++k) {
const int value = histo->distribution[k];
if (value > 0) {
if (value > max_value) max_value = value;
last_non_zero = k;
}
}
// 'alpha' will later be clipped to [0..MAX_ALPHA] range, clamping outer
// values which happen to be mostly noise. This leaves the maximum precision
// for handling the useful small values which contribute most.
alpha = (max_value > 1) ? ALPHA_SCALE * last_non_zero / max_value : 0;
return alpha;
}
static void MergeHistograms(const VP8Histogram* const in,
VP8Histogram* const out) {
int i;
for (i = 0; i <= MAX_COEFF_THRESH; ++i) {
out->distribution[i] += in->distribution[i];
}
}
//------------------------------------------------------------------------------
// Simplified k-Means, to assign Nb segments based on alpha-histogram
static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
static void AssignSegments(VP8Encoder* const enc,
const int alphas[MAX_ALPHA + 1]) {
const int nb = enc->segment_hdr_.num_segments_;
int centers[NUM_MB_SEGMENTS];
int weighted_average = 0;
int map[256];
int map[MAX_ALPHA + 1];
int a, n, k;
int min_a = 0, max_a = 255, range_a;
int min_a = 0, max_a = MAX_ALPHA, range_a;
// 'int' type is ok for histo, and won't overflow
int accum[NUM_MB_SEGMENTS], dist_accum[NUM_MB_SEGMENTS];
// bracket the input
for (n = 0; n < 256 && alphas[n] == 0; ++n) {}
for (n = 0; n <= MAX_ALPHA && alphas[n] == 0; ++n) {}
min_a = n;
for (n = 255; n > min_a && alphas[n] == 0; --n) {}
for (n = MAX_ALPHA; n > min_a && alphas[n] == 0; --n) {}
max_a = n;
range_a = max_a - min_a;
@ -210,7 +247,7 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
VP8MBInfo* const mb = &enc->mb_info_[n];
const int alpha = mb->alpha_;
mb->segment_ = map[alpha];
mb->alpha_ = centers[map[alpha]]; // just for the record.
mb->alpha_ = centers[map[alpha]]; // for the record.
}
if (nb > 1) {
@ -236,15 +273,19 @@ static void AssignSegments(VP8Encoder* const enc, const int alphas[256]) {
static int MBAnalyzeBestIntra16Mode(VP8EncIterator* const it) {
const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA16_MODE : 4;
int mode;
int best_alpha = -1;
int best_alpha = DEFAULT_ALPHA;
int best_mode = 0;
VP8MakeLuma16Preds(it);
for (mode = 0; mode < max_mode; ++mode) {
const int alpha = VP8CollectHistogram(it->yuv_in_ + Y_OFF,
it->yuv_p_ + VP8I16ModeOffsets[mode],
0, 16);
if (alpha > best_alpha) {
VP8Histogram histo = { { 0 } };
int alpha;
VP8CollectHistogram(it->yuv_in_ + Y_OFF,
it->yuv_p_ + VP8I16ModeOffsets[mode],
0, 16, &histo);
alpha = GetAlpha(&histo);
if (IS_BETTER_ALPHA(alpha, best_alpha)) {
best_alpha = alpha;
best_mode = mode;
}
@ -257,45 +298,58 @@ static int MBAnalyzeBestIntra4Mode(VP8EncIterator* const it,
int best_alpha) {
uint8_t modes[16];
const int max_mode = (it->enc_->method_ >= 3) ? MAX_INTRA4_MODE : NUM_BMODES;
int i4_alpha = 0;
int i4_alpha;
VP8Histogram total_histo = { { 0 } };
int cur_histo = 0;
VP8IteratorStartI4(it);
do {
int mode;
int best_mode_alpha = -1;
int best_mode_alpha = DEFAULT_ALPHA;
VP8Histogram histos[2];
const uint8_t* const src = it->yuv_in_ + Y_OFF + VP8Scan[it->i4_];
VP8MakeIntra4Preds(it);
for (mode = 0; mode < max_mode; ++mode) {
const int alpha = VP8CollectHistogram(src,
it->yuv_p_ + VP8I4ModeOffsets[mode],
0, 1);
if (alpha > best_mode_alpha) {
int alpha;
memset(&histos[cur_histo], 0, sizeof(histos[cur_histo]));
VP8CollectHistogram(src, it->yuv_p_ + VP8I4ModeOffsets[mode],
0, 1, &histos[cur_histo]);
alpha = GetAlpha(&histos[cur_histo]);
if (IS_BETTER_ALPHA(alpha, best_mode_alpha)) {
best_mode_alpha = alpha;
modes[it->i4_] = mode;
cur_histo ^= 1; // keep track of best histo so far.
}
}
i4_alpha += best_mode_alpha;
// accumulate best histogram
MergeHistograms(&histos[cur_histo ^ 1], &total_histo);
// Note: we reuse the original samples for predictors
} while (VP8IteratorRotateI4(it, it->yuv_in_ + Y_OFF));
if (i4_alpha > best_alpha) {
i4_alpha = GetAlpha(&total_histo);
if (IS_BETTER_ALPHA(i4_alpha, best_alpha)) {
VP8SetIntra4Mode(it, modes);
best_alpha = ClipAlpha(i4_alpha);
best_alpha = i4_alpha;
}
return best_alpha;
}
static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
int best_alpha = -1;
int best_alpha = DEFAULT_ALPHA;
int best_mode = 0;
const int max_mode = (it->enc_->method_ >= 3) ? MAX_UV_MODE : 4;
int mode;
VP8MakeChroma8Preds(it);
for (mode = 0; mode < max_mode; ++mode) {
const int alpha = VP8CollectHistogram(it->yuv_in_ + U_OFF,
it->yuv_p_ + VP8UVModeOffsets[mode],
16, 16 + 4 + 4);
if (alpha > best_alpha) {
VP8Histogram histo = { { 0 } };
int alpha;
VP8CollectHistogram(it->yuv_in_ + U_OFF,
it->yuv_p_ + VP8UVModeOffsets[mode],
16, 16 + 4 + 4, &histo);
alpha = GetAlpha(&histo);
if (IS_BETTER_ALPHA(alpha, best_alpha)) {
best_alpha = alpha;
best_mode = mode;
}
@ -305,7 +359,7 @@ static int MBAnalyzeBestUVMode(VP8EncIterator* const it) {
}
static void MBAnalyze(VP8EncIterator* const it,
int alphas[256], int* const uv_alpha) {
int alphas[MAX_ALPHA + 1], int* const uv_alpha) {
const VP8Encoder* const enc = it->enc_;
int best_alpha, best_uv_alpha;
@ -324,10 +378,11 @@ static void MBAnalyze(VP8EncIterator* const it,
best_uv_alpha = MBAnalyzeBestUVMode(it);
// Final susceptibility mix
best_alpha = (best_alpha + best_uv_alpha + 1) / 2;
best_alpha = (3 * best_alpha + best_uv_alpha + 2) >> 2;
best_alpha = FinalAlphaValue(best_alpha);
alphas[best_alpha]++;
*uv_alpha += best_uv_alpha;
it->mb_->alpha_ = best_alpha; // Informative only.
it->mb_->alpha_ = best_alpha; // for later remapping.
}
//------------------------------------------------------------------------------
@ -342,7 +397,7 @@ static void MBAnalyze(VP8EncIterator* const it,
int VP8EncAnalyze(VP8Encoder* const enc) {
int ok = 1;
int alphas[256] = { 0 };
int alphas[MAX_ALPHA + 1] = { 0 };
VP8EncIterator it;
VP8IteratorInit(enc, &it);