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// Copyright (c) the JPEG XL 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.
// Edge-preserving smoothing: weighted average based on L1 patch similarity.
#include "lib/jxl/epf.h"
#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <cstring>
#include "lib/jxl/ac_strategy.h"
#include "lib/jxl/base/compiler_specific.h"
#include "lib/jxl/base/rect.h"
#include "lib/jxl/base/status.h"
#include "lib/jxl/dec_cache.h"
#include "lib/jxl/loop_filter.h"
#include "lib/jxl/quantizer.h"
namespace jxl {
// Mirror n floats starting at *p and store them before p.
JXL_INLINE void LeftMirror(float* p, size_t n) {
for (size_t i = 0; i < n; i++) {
*(p - 1 - i) = p[i];
}
}
// Mirror n floats starting at *(p - n) and store them at *p.
JXL_INLINE void RightMirror(float* p, size_t n) {
for (size_t i = 0; i < n; i++) {
p[i] = *(p - 1 - i);
}
}
Status ComputeSigma(const LoopFilter& lf, const Rect& block_rect,
PassesDecoderState* state) {
JXL_ENSURE(lf.epf_iters > 0);
const AcStrategyImage& ac_strategy = state->shared->ac_strategy;
const float quant_scale = state->shared->quantizer.Scale();
const size_t sigma_stride = state->sigma.PixelsPerRow();
const size_t sharpness_stride = state->shared->epf_sharpness.PixelsPerRow();
for (size_t by = 0; by < block_rect.ysize(); ++by) {
float* JXL_RESTRICT sigma_row = block_rect.Row(&state->sigma, by);
const uint8_t* JXL_RESTRICT sharpness_row =
block_rect.ConstRow(state->shared->epf_sharpness, by);
AcStrategyRow acs_row = ac_strategy.ConstRow(block_rect, by);
const int32_t* const JXL_RESTRICT row_quant =
block_rect.ConstRow(state->shared->raw_quant_field, by);
for (size_t bx = 0; bx < block_rect.xsize(); bx++) {
AcStrategy acs = acs_row[bx];
size_t llf_x = acs.covered_blocks_x();
if (!acs.IsFirstBlock()) continue;
// quant_scale is smaller for low quality.
// quant_scale is roughly 0.08 / butteraugli score.
//
// row_quant is smaller for low quality.
// row_quant is a quantization multiplier of form 1.0 /
// row_quant[bx]
//
// lf.epf_quant_mul is a parameter in the format
// kInvSigmaNum is a constant
float sigma_quant =
lf.epf_quant_mul / (quant_scale * row_quant[bx] * kInvSigmaNum);
for (size_t iy = 0; iy < acs.covered_blocks_y(); iy++) {
for (size_t ix = 0; ix < acs.covered_blocks_x(); ix++) {
float sigma =
sigma_quant *
lf.epf_sharp_lut[sharpness_row[bx + ix + iy * sharpness_stride]];
// Avoid infinities.
sigma = std::min(-1e-4f, sigma); // TODO(veluca): remove this.
sigma_row[bx + ix + kSigmaPadding +
(iy + kSigmaPadding) * sigma_stride] = 1.0f / sigma;
}
}
// TODO(veluca): remove this padding.
// Left padding with mirroring.
if (bx + block_rect.x0() == 0) {
for (size_t iy = 0; iy < acs.covered_blocks_y(); iy++) {
LeftMirror(
sigma_row + kSigmaPadding + (iy + kSigmaPadding) * sigma_stride,
kSigmaBorder);
}
}
// Right padding with mirroring.
if (bx + block_rect.x0() + llf_x ==
state->shared->frame_dim.xsize_blocks) {
for (size_t iy = 0; iy < acs.covered_blocks_y(); iy++) {
RightMirror(sigma_row + kSigmaPadding + bx + llf_x +
(iy + kSigmaPadding) * sigma_stride,
kSigmaBorder);
}
}
// Offsets for row copying, in blocks.
size_t offset_before = bx + block_rect.x0() == 0 ? 1 : bx + kSigmaPadding;
size_t offset_after =
bx + block_rect.x0() + llf_x == state->shared->frame_dim.xsize_blocks
? kSigmaPadding + llf_x + bx + kSigmaBorder
: kSigmaPadding + llf_x + bx;
size_t num = offset_after - offset_before;
// Above
if (by + block_rect.y0() == 0) {
for (size_t iy = 0; iy < kSigmaBorder; iy++) {
memcpy(
sigma_row + offset_before +
(kSigmaPadding - 1 - iy) * sigma_stride,
sigma_row + offset_before + (kSigmaPadding + iy) * sigma_stride,
num * sizeof(*sigma_row));
}
}
// Below
if (by + block_rect.y0() + acs.covered_blocks_y() ==
state->shared->frame_dim.ysize_blocks) {
for (size_t iy = 0; iy < kSigmaBorder; iy++) {
memcpy(
sigma_row + offset_before +
sigma_stride * (acs.covered_blocks_y() + kSigmaPadding + iy),
sigma_row + offset_before +
sigma_stride *
(acs.covered_blocks_y() + kSigmaPadding - 1 - iy),
num * sizeof(*sigma_row));
}
}
}
}
return true;
}
} // namespace jxl