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godotengine
GitHub Repository: godotengine/godot
Path: blob/master/thirdparty/libwebp/src/utils/quant_levels_dec_utils.c
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// Copyright 2013 Google Inc. All Rights Reserved.
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//
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// Use of this source code is governed by a BSD-style license
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// that can be found in the COPYING file in the root of the source
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// tree. An additional intellectual property rights grant can be found
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// in the file PATENTS. All contributing project authors may
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// be found in the AUTHORS file in the root of the source tree.
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// -----------------------------------------------------------------------------
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//
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// Implement gradient smoothing: we replace a current alpha value by its
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// surrounding average if it's close enough (that is: the change will be less
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// than the minimum distance between two quantized level).
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// We use sliding window for computing the 2d moving average.
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//
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// Author: Skal ([email protected])
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#include "src/utils/quant_levels_dec_utils.h"
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#include <string.h> // for memset
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#include "src/utils/utils.h"
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// #define USE_DITHERING // uncomment to enable ordered dithering (not vital)
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#define FIX 16 // fix-point precision for averaging
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#define LFIX 2 // extra precision for look-up table
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#define LUT_SIZE ((1 << (8 + LFIX)) - 1) // look-up table size
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#if defined(USE_DITHERING)
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#define DFIX 4 // extra precision for ordered dithering
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#define DSIZE 4 // dithering size (must be a power of two)
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// cf. https://en.wikipedia.org/wiki/Ordered_dithering
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static const uint8_t kOrderedDither[DSIZE][DSIZE] = {
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{ 0, 8, 2, 10 }, // coefficients are in DFIX fixed-point precision
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{ 12, 4, 14, 6 },
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{ 3, 11, 1, 9 },
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{ 15, 7, 13, 5 }
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};
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#else
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#define DFIX 0
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#endif
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typedef struct {
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int width_, height_; // dimension
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int stride_; // stride in bytes
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int row_; // current input row being processed
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uint8_t* src_; // input pointer
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uint8_t* dst_; // output pointer
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int radius_; // filter radius (=delay)
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int scale_; // normalization factor, in FIX bits precision
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void* mem_; // all memory
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// various scratch buffers
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uint16_t* start_;
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uint16_t* cur_;
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uint16_t* end_;
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uint16_t* top_;
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uint16_t* average_;
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// input levels distribution
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int num_levels_; // number of quantized levels
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int min_, max_; // min and max level values
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int min_level_dist_; // smallest distance between two consecutive levels
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int16_t* correction_; // size = 1 + 2*LUT_SIZE -> ~4k memory
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} SmoothParams;
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//------------------------------------------------------------------------------
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#define CLIP_8b_MASK (int)(~0U << (8 + DFIX))
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static WEBP_INLINE uint8_t clip_8b(int v) {
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return (!(v & CLIP_8b_MASK)) ? (uint8_t)(v >> DFIX) : (v < 0) ? 0u : 255u;
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}
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#undef CLIP_8b_MASK
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// vertical accumulation
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static void VFilter(SmoothParams* const p) {
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const uint8_t* src = p->src_;
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const int w = p->width_;
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uint16_t* const cur = p->cur_;
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const uint16_t* const top = p->top_;
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uint16_t* const out = p->end_;
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uint16_t sum = 0; // all arithmetic is modulo 16bit
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int x;
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for (x = 0; x < w; ++x) {
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uint16_t new_value;
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sum += src[x];
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new_value = top[x] + sum;
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out[x] = new_value - cur[x]; // vertical sum of 'r' pixels.
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cur[x] = new_value;
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}
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// move input pointers one row down
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p->top_ = p->cur_;
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p->cur_ += w;
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if (p->cur_ == p->end_) p->cur_ = p->start_; // roll-over
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// We replicate edges, as it's somewhat easier as a boundary condition.
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// That's why we don't update the 'src' pointer on top/bottom area:
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if (p->row_ >= 0 && p->row_ < p->height_ - 1) {
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p->src_ += p->stride_;
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}
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}
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// horizontal accumulation. We use mirror replication of missing pixels, as it's
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// a little easier to implement (surprisingly).
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static void HFilter(SmoothParams* const p) {
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const uint16_t* const in = p->end_;
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uint16_t* const out = p->average_;
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const uint32_t scale = p->scale_;
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const int w = p->width_;
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const int r = p->radius_;
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int x;
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for (x = 0; x <= r; ++x) { // left mirroring
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const uint16_t delta = in[x + r - 1] + in[r - x];
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out[x] = (delta * scale) >> FIX;
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}
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for (; x < w - r; ++x) { // bulk middle run
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const uint16_t delta = in[x + r] - in[x - r - 1];
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out[x] = (delta * scale) >> FIX;
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}
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for (; x < w; ++x) { // right mirroring
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const uint16_t delta =
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2 * in[w - 1] - in[2 * w - 2 - r - x] - in[x - r - 1];
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out[x] = (delta * scale) >> FIX;
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}
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}
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// emit one filtered output row
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static void ApplyFilter(SmoothParams* const p) {
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const uint16_t* const average = p->average_;
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const int w = p->width_;
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const int16_t* const correction = p->correction_;
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#if defined(USE_DITHERING)
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const uint8_t* const dither = kOrderedDither[p->row_ % DSIZE];
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#endif
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uint8_t* const dst = p->dst_;
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int x;
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for (x = 0; x < w; ++x) {
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const int v = dst[x];
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if (v < p->max_ && v > p->min_) {
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const int c = (v << DFIX) + correction[average[x] - (v << LFIX)];
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#if defined(USE_DITHERING)
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dst[x] = clip_8b(c + dither[x % DSIZE]);
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#else
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dst[x] = clip_8b(c);
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#endif
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}
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}
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p->dst_ += p->stride_; // advance output pointer
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}
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//------------------------------------------------------------------------------
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// Initialize correction table
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static void InitCorrectionLUT(int16_t* const lut, int min_dist) {
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// The correction curve is:
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// f(x) = x for x <= threshold2
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// f(x) = 0 for x >= threshold1
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// and a linear interpolation for range x=[threshold2, threshold1]
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// (along with f(-x) = -f(x) symmetry).
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// Note that: threshold2 = 3/4 * threshold1
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const int threshold1 = min_dist << LFIX;
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const int threshold2 = (3 * threshold1) >> 2;
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const int max_threshold = threshold2 << DFIX;
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const int delta = threshold1 - threshold2;
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int i;
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for (i = 1; i <= LUT_SIZE; ++i) {
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int c = (i <= threshold2) ? (i << DFIX)
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: (i < threshold1) ? max_threshold * (threshold1 - i) / delta
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: 0;
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c >>= LFIX;
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lut[+i] = +c;
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lut[-i] = -c;
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}
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lut[0] = 0;
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}
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static void CountLevels(SmoothParams* const p) {
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int i, j, last_level;
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uint8_t used_levels[256] = { 0 };
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const uint8_t* data = p->src_;
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p->min_ = 255;
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p->max_ = 0;
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for (j = 0; j < p->height_; ++j) {
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for (i = 0; i < p->width_; ++i) {
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const int v = data[i];
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if (v < p->min_) p->min_ = v;
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if (v > p->max_) p->max_ = v;
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used_levels[v] = 1;
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}
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data += p->stride_;
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}
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// Compute the mininum distance between two non-zero levels.
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p->min_level_dist_ = p->max_ - p->min_;
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last_level = -1;
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for (i = 0; i < 256; ++i) {
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if (used_levels[i]) {
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++p->num_levels_;
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if (last_level >= 0) {
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const int level_dist = i - last_level;
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if (level_dist < p->min_level_dist_) {
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p->min_level_dist_ = level_dist;
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}
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}
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last_level = i;
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}
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}
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}
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// Initialize all params.
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static int InitParams(uint8_t* const data, int width, int height, int stride,
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int radius, SmoothParams* const p) {
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const int R = 2 * radius + 1; // total size of the kernel
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const size_t size_scratch_m = (R + 1) * width * sizeof(*p->start_);
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const size_t size_m = width * sizeof(*p->average_);
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const size_t size_lut = (1 + 2 * LUT_SIZE) * sizeof(*p->correction_);
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const size_t total_size = size_scratch_m + size_m + size_lut;
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uint8_t* mem = (uint8_t*)WebPSafeMalloc(1U, total_size);
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if (mem == NULL) return 0;
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p->mem_ = (void*)mem;
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p->start_ = (uint16_t*)mem;
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p->cur_ = p->start_;
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p->end_ = p->start_ + R * width;
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p->top_ = p->end_ - width;
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memset(p->top_, 0, width * sizeof(*p->top_));
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mem += size_scratch_m;
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p->average_ = (uint16_t*)mem;
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mem += size_m;
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p->width_ = width;
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p->height_ = height;
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p->stride_ = stride;
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p->src_ = data;
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p->dst_ = data;
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p->radius_ = radius;
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p->scale_ = (1 << (FIX + LFIX)) / (R * R); // normalization constant
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p->row_ = -radius;
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// analyze the input distribution so we can best-fit the threshold
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CountLevels(p);
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// correction table
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p->correction_ = ((int16_t*)mem) + LUT_SIZE;
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InitCorrectionLUT(p->correction_, p->min_level_dist_);
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return 1;
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}
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static void CleanupParams(SmoothParams* const p) {
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WebPSafeFree(p->mem_);
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}
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int WebPDequantizeLevels(uint8_t* const data, int width, int height, int stride,
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int strength) {
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int radius = 4 * strength / 100;
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if (strength < 0 || strength > 100) return 0;
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if (data == NULL || width <= 0 || height <= 0) return 0; // bad params
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// limit the filter size to not exceed the image dimensions
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if (2 * radius + 1 > width) radius = (width - 1) >> 1;
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if (2 * radius + 1 > height) radius = (height - 1) >> 1;
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if (radius > 0) {
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SmoothParams p;
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memset(&p, 0, sizeof(p));
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if (!InitParams(data, width, height, stride, radius, &p)) return 0;
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if (p.num_levels_ > 2) {
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for (; p.row_ < p.height_; ++p.row_) {
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VFilter(&p); // accumulate average of input
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// Need to wait few rows in order to prime the filter,
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// before emitting some output.
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if (p.row_ >= p.radius_) {
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HFilter(&p);
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ApplyFilter(&p);
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}
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}
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}
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CleanupParams(&p);
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}
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return 1;
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}
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