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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.
#ifndef LIB_JXL_CONVOLVE_H_
#define LIB_JXL_CONVOLVE_H_
// 2D convolution.
#include <stddef.h>
#include <stdint.h>
#include "lib/jxl/base/data_parallel.h"
#include "lib/jxl/image.h"
namespace jxl {
// No valid values outside [0, xsize), but the strategy may still safely load
// the preceding vector, and/or round xsize up to the vector lane count. This
// avoids needing PadImage.
// Requires xsize >= kConvolveLanes + kConvolveMaxRadius.
static constexpr size_t kConvolveMaxRadius = 3;
// Weights must already be normalized.
struct WeightsSymmetric3 {
// d r d (each replicated 4x)
// r c r
// d r d
float c[4];
float r[4];
float d[4];
};
struct WeightsSymmetric5 {
// The lower-right quadrant is: c r R (each replicated 4x)
// r d L
// R L D
float c[4];
float r[4];
float R[4];
float d[4];
float D[4];
float L[4];
};
// Weights for separable 5x5 filters (typically but not necessarily the same
// values for horizontal and vertical directions). The kernel must already be
// normalized, but note that values for negative offsets are omitted, so the
// given values do not sum to 1.
struct WeightsSeparable5 {
// Horizontal 1D, distances 0..2 (each replicated 4x)
float horz[3 * 4];
float vert[3 * 4];
};
// Weights for separable 7x7 filters (typically but not necessarily the same
// values for horizontal and vertical directions). The kernel must already be
// normalized, but note that values for negative offsets are omitted, so the
// given values do not sum to 1.
//
// NOTE: for >= 7x7 Gaussian kernels, it is faster to use FastGaussian instead,
// at least when images exceed the L1 cache size.
struct WeightsSeparable7 {
// Horizontal 1D, distances 0..3 (each replicated 4x)
float horz[4 * 4];
float vert[4 * 4];
};
const WeightsSymmetric3& WeightsSymmetric3Lowpass();
const WeightsSeparable5& WeightsSeparable5Lowpass();
const WeightsSymmetric5& WeightsSymmetric5Lowpass();
void SlowSymmetric3(const ImageF& in, const Rect& rect,
const WeightsSymmetric3& weights, ThreadPool* pool,
ImageF* JXL_RESTRICT out);
void SlowSymmetric3(const Image3F& in, const Rect& rect,
const WeightsSymmetric3& weights, ThreadPool* pool,
Image3F* JXL_RESTRICT out);
void SlowSeparable5(const ImageF& in, const Rect& rect,
const WeightsSeparable5& weights, ThreadPool* pool,
ImageF* out);
void SlowSeparable5(const Image3F& in, const Rect& rect,
const WeightsSeparable5& weights, ThreadPool* pool,
Image3F* out);
void SlowSeparable7(const ImageF& in, const Rect& rect,
const WeightsSeparable7& weights, ThreadPool* pool,
ImageF* out);
void SlowSeparable7(const Image3F& in, const Rect& rect,
const WeightsSeparable7& weights, ThreadPool* pool,
Image3F* out);
void SlowLaplacian5(const ImageF& in, const Rect& rect, ThreadPool* pool,
ImageF* out);
void SlowLaplacian5(const Image3F& in, const Rect& rect, ThreadPool* pool,
Image3F* out);
void Symmetric3(const ImageF& in, const Rect& rect,
const WeightsSymmetric3& weights, ThreadPool* pool,
ImageF* out);
void Symmetric5(const ImageF& in, const Rect& rect,
const WeightsSymmetric5& weights, ThreadPool* pool,
ImageF* JXL_RESTRICT out);
void Symmetric5_3(const Image3F& in, const Rect& rect,
const WeightsSymmetric5& weights, ThreadPool* pool,
Image3F* JXL_RESTRICT out);
void Separable5(const ImageF& in, const Rect& rect,
const WeightsSeparable5& weights, ThreadPool* pool,
ImageF* out);
void Separable5_3(const Image3F& in, const Rect& rect,
const WeightsSeparable5& weights, ThreadPool* pool,
Image3F* out);
void Separable7(const ImageF& in, const Rect& rect,
const WeightsSeparable7& weights, ThreadPool* pool,
ImageF* out);
void Separable7_3(const Image3F& in, const Rect& rect,
const WeightsSeparable7& weights, ThreadPool* pool,
Image3F* out);
} // namespace jxl
#endif // LIB_JXL_CONVOLVE_H_
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