enc_xyb.cc - mozsearch

// 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.

#include "lib/jxl/enc_xyb.h"

#include <jxl/memory_manager.h>

#include <algorithm>

#include <cstdlib>

#undef HWY_TARGET_INCLUDE

#define HWY_TARGET_INCLUDE "lib/jxl/enc_xyb.cc"

#include <hwy/foreach_target.h>

#include <hwy/highway.h>

#include "lib/jxl/base/compiler_specific.h"

#include "lib/jxl/base/data_parallel.h"

#include "lib/jxl/base/fast_math-inl.h"

#include "lib/jxl/base/rect.h"

#include "lib/jxl/base/status.h"

#include "lib/jxl/cms/opsin_params.h"

#include "lib/jxl/cms/transfer_functions-inl.h"

#include "lib/jxl/color_encoding_internal.h"

#include "lib/jxl/enc_image_bundle.h"

#include "lib/jxl/image_bundle.h"

#include "lib/jxl/image_ops.h"

HWY_BEFORE_NAMESPACE();

namespace jxl {

namespace HWY_NAMESPACE {

// These templates are not found via ADL.

using hwy::HWY_NAMESPACE::Add;

using hwy::HWY_NAMESPACE::Mul;

using hwy::HWY_NAMESPACE::MulAdd;

using hwy::HWY_NAMESPACE::Sub;

using hwy::HWY_NAMESPACE::ZeroIfNegative;

// 4x3 matrix * 3x1 SIMD vectors

template <class V>

JXL_INLINE void OpsinAbsorbance(const V r, const V g, const V b,

                                const float* JXL_RESTRICT premul_absorb,

                                V* JXL_RESTRICT mixed0, V* JXL_RESTRICT mixed1,

                                V* JXL_RESTRICT mixed2) {

  const float* bias = jxl::cms::kOpsinAbsorbanceBias.data();

  const HWY_FULL(float) d;

  const size_t N = Lanes(d);

  const auto m0 = Load(d, premul_absorb + 0 * N);

  const auto m1 = Load(d, premul_absorb + 1 * N);

  const auto m2 = Load(d, premul_absorb + 2 * N);

  const auto m3 = Load(d, premul_absorb + 3 * N);

  const auto m4 = Load(d, premul_absorb + 4 * N);

  const auto m5 = Load(d, premul_absorb + 5 * N);

  const auto m6 = Load(d, premul_absorb + 6 * N);

  const auto m7 = Load(d, premul_absorb + 7 * N);

  const auto m8 = Load(d, premul_absorb + 8 * N);

  *mixed0 = MulAdd(m0, r, MulAdd(m1, g, MulAdd(m2, b, Set(d, bias[0]))));

  *mixed1 = MulAdd(m3, r, MulAdd(m4, g, MulAdd(m5, b, Set(d, bias[1]))));

  *mixed2 = MulAdd(m6, r, MulAdd(m7, g, MulAdd(m8, b, Set(d, bias[2]))));

template <class V>

void StoreXYB(const V r, V g, const V b, float* JXL_RESTRICT valx,

              float* JXL_RESTRICT valy, float* JXL_RESTRICT valz) {

  const HWY_FULL(float) d;

  const V half = Set(d, 0.5f);

  Store(Mul(half, Sub(r, g)), d, valx);

  Store(Mul(half, Add(r, g)), d, valy);

  Store(b, d, valz);

// Converts one RGB vector to XYB.

template <class V>

void LinearRGBToXYB(const V r, const V g, const V b,

                    const float* JXL_RESTRICT premul_absorb,

                    float* JXL_RESTRICT valx, float* JXL_RESTRICT valy,

                    float* JXL_RESTRICT valz) {

  V mixed0;

  V mixed1;

  V mixed2;

  OpsinAbsorbance(r, g, b, premul_absorb, &mixed0, &mixed1, &mixed2);

  // mixed* should be non-negative even for wide-gamut, so clamp to zero.

  mixed0 = ZeroIfNegative(mixed0);

  mixed1 = ZeroIfNegative(mixed1);

  mixed2 = ZeroIfNegative(mixed2);

  const HWY_FULL(float) d;

  const size_t N = Lanes(d);

  mixed0 = CubeRootAndAdd(mixed0, Load(d, premul_absorb + 9 * N));

  mixed1 = CubeRootAndAdd(mixed1, Load(d, premul_absorb + 10 * N));

  mixed2 = CubeRootAndAdd(mixed2, Load(d, premul_absorb + 11 * N));

  StoreXYB(mixed0, mixed1, mixed2, valx, valy, valz);

  // For wide-gamut inputs, r/g/b and valx (but not y/z) are often negative.

void LinearRGBRowToXYB(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,

                       float* JXL_RESTRICT row2,

                       const float* JXL_RESTRICT premul_absorb, size_t xsize) {

  const HWY_FULL(float) d;

  for (size_t x = 0; x < xsize; x += Lanes(d)) {

    const auto r = Load(d, row0 + x);

    const auto g = Load(d, row1 + x);

    const auto b = Load(d, row2 + x);

    LinearRGBToXYB(r, g, b, premul_absorb, row0 + x, row1 + x, row2 + x);

// Input/output uses the codec.h scaling: nominally 0-1 if in-gamut.

template <class V>

V LinearFromSRGB(V encoded) {

  return TF_SRGB().DisplayFromEncoded(encoded);

Status LinearSRGBToXYB(const float* JXL_RESTRICT premul_absorb,

                       ThreadPool* pool, Image3F* JXL_RESTRICT image) {

  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;

  const auto process_row = [&](const uint32_t task,

                               size_t /*thread*/) -> Status {

    const size_t y = static_cast<size_t>(task);

    float* JXL_RESTRICT row0 = image->PlaneRow(0, y);

    float* JXL_RESTRICT row1 = image->PlaneRow(1, y);

    float* JXL_RESTRICT row2 = image->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {

      const auto in_r = Load(d, row0 + x);

      const auto in_g = Load(d, row1 + x);

      const auto in_b = Load(d, row2 + x);

      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row0 + x, row1 + x,

                     row2 + x);

    return true;

};

  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),

                                ThreadPool::NoInit, process_row,

                                "LinearToXYB"));

  return true;

Status SRGBToXYB(const float* JXL_RESTRICT premul_absorb, ThreadPool* pool,

                 Image3F* JXL_RESTRICT image) {

  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;

  const auto process_row = [&](const uint32_t task,

                               size_t /*thread*/) -> Status {

    const size_t y = static_cast<size_t>(task);

    float* JXL_RESTRICT row0 = image->PlaneRow(0, y);

    float* JXL_RESTRICT row1 = image->PlaneRow(1, y);

    float* JXL_RESTRICT row2 = image->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {

      const auto in_r = LinearFromSRGB(Load(d, row0 + x));

      const auto in_g = LinearFromSRGB(Load(d, row1 + x));

      const auto in_b = LinearFromSRGB(Load(d, row2 + x));

      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row0 + x, row1 + x,

                     row2 + x);

    return true;

};

  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),

                                ThreadPool::NoInit, process_row, "SRGBToXYB"));

  return true;

Status SRGBToXYBAndLinear(const float* JXL_RESTRICT premul_absorb,

                          ThreadPool* pool, Image3F* JXL_RESTRICT image,

                          Image3F* JXL_RESTRICT linear) {

  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;

  const auto process_row = [&](const uint32_t task,

                               size_t /*thread*/) -> Status {

    const size_t y = static_cast<size_t>(task);

    float* JXL_RESTRICT row_image0 = image->PlaneRow(0, y);

    float* JXL_RESTRICT row_image1 = image->PlaneRow(1, y);

    float* JXL_RESTRICT row_image2 = image->PlaneRow(2, y);

    float* JXL_RESTRICT row_linear0 = linear->PlaneRow(0, y);

    float* JXL_RESTRICT row_linear1 = linear->PlaneRow(1, y);

    float* JXL_RESTRICT row_linear2 = linear->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {

      const auto in_r = LinearFromSRGB(Load(d, row_image0 + x));

      const auto in_g = LinearFromSRGB(Load(d, row_image1 + x));

      const auto in_b = LinearFromSRGB(Load(d, row_image2 + x));

      Store(in_r, d, row_linear0 + x);

      Store(in_g, d, row_linear1 + x);

      Store(in_b, d, row_linear2 + x);

      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row_image0 + x,

                     row_image1 + x, row_image2 + x);

    return true;

};

  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),

                                ThreadPool::NoInit, process_row,

                                "SRGBToXYBAndLinear"));

  return true;

void ComputePremulAbsorb(float intensity_target, float* premul_absorb) {

  const HWY_FULL(float) d;

  const size_t N = Lanes(d);

  const float mul = intensity_target / 255.0f;

  for (size_t j = 0; j < 3; ++j) {

    for (size_t i = 0; i < 3; ++i) {

      const auto absorb = Set(d, jxl::cms::kOpsinAbsorbanceMatrix[j][i] * mul);

      Store(absorb, d, premul_absorb + (j * 3 + i) * N);

  for (size_t i = 0; i < 3; ++i) {

    const auto neg_bias_cbrt =

        Set(d, -cbrtf(jxl::cms::kOpsinAbsorbanceBias[i]));

    Store(neg_bias_cbrt, d, premul_absorb + (9 + i) * N);

// This is different from Butteraugli's OpsinDynamicsImage() in the sense that

// it does not contain a sensitivity multiplier based on the blurred image.

Status ToXYB(const ColorEncoding& c_current, float intensity_target,

             const ImageF* black, ThreadPool* pool, Image3F* JXL_RESTRICT image,

             const JxlCmsInterface& cms, Image3F* const JXL_RESTRICT linear) {

  if (black) JXL_ENSURE(SameSize(*image, *black));

  if (linear) JXL_ENSURE(SameSize(*image, *linear));

  const HWY_FULL(float) d;

  // Pre-broadcasted constants

  HWY_ALIGN float premul_absorb[MaxLanes(d) * 12];

  ComputePremulAbsorb(intensity_target, premul_absorb);

  const bool want_linear = linear != nullptr;

  const ColorEncoding& c_linear_srgb =

      ColorEncoding::LinearSRGB(c_current.IsGray());

  // Linear sRGB inputs are rare but can be useful for the fastest encoders, for

  // which undoing the sRGB transfer function would be a large part of the cost.

  if (c_linear_srgb.SameColorEncoding(c_current)) {

    // This only happens if kitten or slower, moving ImageBundle might be

    // possible but the encoder is much slower than this copy.

    if (want_linear) {

      JXL_RETURN_IF_ERROR(CopyImageTo(*image, linear));

    JXL_RETURN_IF_ERROR(LinearSRGBToXYB(premul_absorb, pool, image));

    return true;

  // Common case: already sRGB, can avoid the color transform

  if (c_current.IsSRGB()) {

    // Common case: can avoid allocating/copying

    if (want_linear) {

      // Slow encoder also wants linear sRGB.

      JXL_RETURN_IF_ERROR(

          SRGBToXYBAndLinear(premul_absorb, pool, image, linear));

    } else {

      JXL_RETURN_IF_ERROR(SRGBToXYB(premul_absorb, pool, image));

    return true;

  JXL_RETURN_IF_ERROR(ApplyColorTransform(

      c_current, intensity_target, *image, black, Rect(*image), c_linear_srgb,

      cms, pool, want_linear ? linear : image));

  if (want_linear) {

    JXL_RETURN_IF_ERROR(CopyImageTo(*linear, image));

  JXL_RETURN_IF_ERROR(LinearSRGBToXYB(premul_absorb, pool, image));

  return true;

// Transform RGB to YCbCr.

// Could be performed in-place (i.e. Y, Cb and Cr could alias R, B and B).

Status RgbToYcbcr(const ImageF& r_plane, const ImageF& g_plane,

                  const ImageF& b_plane, ImageF* y_plane, ImageF* cb_plane,

                  ImageF* cr_plane, ThreadPool* pool) {

  const HWY_FULL(float) df;

  const size_t S = Lanes(df);  // Step.

  const size_t xsize = r_plane.xsize();

  const size_t ysize = r_plane.ysize();

  if ((xsize == 0) || (ysize == 0)) return true;

  // Full-range BT.601 as defined by JFIF Clause 7:

  // https://www.itu.int/rec/T-REC-T.871-201105-I/en

  const auto k128 = Set(df, 128.0f / 255);

  const auto kR = Set(df, 0.299f);  // NTSC luma

  const auto kG = Set(df, 0.587f);

  const auto kB = Set(df, 0.114f);

  const auto kAmpR = Set(df, 0.701f);

  const auto kAmpB = Set(df, 0.886f);

  const auto kDiffR = Add(kAmpR, kR);

  const auto kDiffB = Add(kAmpB, kB);

  const auto kNormR = Div(Set(df, 1.0f), (Add(kAmpR, Add(kG, kB))));

  const auto kNormB = Div(Set(df, 1.0f), (Add(kR, Add(kG, kAmpB))));

  constexpr size_t kGroupArea = kGroupDim * kGroupDim;

  const size_t lines_per_group = DivCeil(kGroupArea, xsize);

  const size_t num_stripes = DivCeil(ysize, lines_per_group);

  const auto transform = [&](int idx, int /* thread*/) -> Status {

    const size_t y0 = idx * lines_per_group;

    const size_t y1 = std::min<size_t>(y0 + lines_per_group, ysize);

    for (size_t y = y0; y < y1; ++y) {

      const float* r_row = r_plane.ConstRow(y);

      const float* g_row = g_plane.ConstRow(y);

      const float* b_row = b_plane.ConstRow(y);

      float* y_row = y_plane->Row(y);

      float* cb_row = cb_plane->Row(y);

      float* cr_row = cr_plane->Row(y);

      for (size_t x = 0; x < xsize; x += S) {

        const auto r = Load(df, r_row + x);

        const auto g = Load(df, g_row + x);

        const auto b = Load(df, b_row + x);

        const auto r_base = Mul(r, kR);

        const auto r_diff = Mul(r, kDiffR);

        const auto g_base = Mul(g, kG);

        const auto b_base = Mul(b, kB);

        const auto b_diff = Mul(b, kDiffB);

        const auto y_base = Add(r_base, Add(g_base, b_base));

        const auto y_vec = Sub(y_base, k128);

        const auto cb_vec = Mul(Sub(b_diff, y_base), kNormB);

        const auto cr_vec = Mul(Sub(r_diff, y_base), kNormR);

        Store(y_vec, df, y_row + x);

        Store(cb_vec, df, cb_row + x);

        Store(cr_vec, df, cr_row + x);

    return true;

};

  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<int>(num_stripes),

                                ThreadPool::NoInit, transform, "RgbToYcbCr"));

  return true;

// NOLINTNEXTLINE(google-readability-namespace-comments)

}  // namespace HWY_NAMESPACE

}  // namespace jxl

HWY_AFTER_NAMESPACE();

#if HWY_ONCE

namespace jxl {

HWY_EXPORT(ToXYB);

Status ToXYB(const ColorEncoding& c_current, float intensity_target,

             const ImageF* black, ThreadPool* pool, Image3F* JXL_RESTRICT image,

             const JxlCmsInterface& cms, Image3F* const JXL_RESTRICT linear) {

  return HWY_DYNAMIC_DISPATCH(ToXYB)(c_current, intensity_target, black, pool,

                                     image, cms, linear);

Status ToXYB(const ImageBundle& in, ThreadPool* pool, Image3F* JXL_RESTRICT xyb,

             const JxlCmsInterface& cms, Image3F* JXL_RESTRICT linear) {

  JxlMemoryManager* memory_manager = in.memory_manager();

  JXL_ASSIGN_OR_RETURN(*xyb,

                       Image3F::Create(memory_manager, in.xsize(), in.ysize()));

  JXL_RETURN_IF_ERROR(CopyImageTo(in.color(), xyb));

  JXL_RETURN_IF_ERROR(ToXYB(in.c_current(), in.metadata()->IntensityTarget(),

                            in.black(), pool, xyb, cms, linear));

  return true;

HWY_EXPORT(LinearRGBRowToXYB);

void LinearRGBRowToXYB(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,

                       float* JXL_RESTRICT row2,

                       const float* JXL_RESTRICT premul_absorb, size_t xsize) {

  HWY_DYNAMIC_DISPATCH(LinearRGBRowToXYB)

  (row0, row1, row2, premul_absorb, xsize);

HWY_EXPORT(ComputePremulAbsorb);

void ComputePremulAbsorb(float intensity_target, float* premul_absorb) {

  HWY_DYNAMIC_DISPATCH(ComputePremulAbsorb)(intensity_target, premul_absorb);

void ScaleXYBRow(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,

                 float* JXL_RESTRICT row2, size_t xsize) {

  for (size_t x = 0; x < xsize; x++) {

    row2[x] = (row2[x] - row1[x] + jxl::cms::kScaledXYBOffset[2]) *

              jxl::cms::kScaledXYBScale[2];

    row0[x] = (row0[x] + jxl::cms::kScaledXYBOffset[0]) *

              jxl::cms::kScaledXYBScale[0];

    row1[x] = (row1[x] + jxl::cms::kScaledXYBOffset[1]) *

              jxl::cms::kScaledXYBScale[1];

void ScaleXYB(Image3F* opsin) {

  for (size_t y = 0; y < opsin->ysize(); y++) {

    float* row0 = opsin->PlaneRow(0, y);

    float* row1 = opsin->PlaneRow(1, y);

    float* row2 = opsin->PlaneRow(2, y);

    ScaleXYBRow(row0, row1, row2, opsin->xsize());

HWY_EXPORT(RgbToYcbcr);

Status RgbToYcbcr(const ImageF& r_plane, const ImageF& g_plane,

                  const ImageF& b_plane, ImageF* y_plane, ImageF* cb_plane,

                  ImageF* cr_plane, ThreadPool* pool) {

  return HWY_DYNAMIC_DISPATCH(RgbToYcbcr)(r_plane, g_plane, b_plane, y_plane,

                                          cb_plane, cr_plane, pool);

}  // namespace jxl

#endif  // HWY_ONCE

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