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/* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
// We are going to be doing so, so many transforms, so descriptive labels are
// critical.
#include "Colorspaces.h"
#include "nsDebug.h"
#include "qcms.h"
namespace mozilla::color {
// tf = { k * linear | linear < b
// { a * pow(linear, 1/g) - (1-a) | linear >= b
float TfFromLinear(const PiecewiseGammaDesc& desc, const float linear) {
if (linear < desc.b) {
return linear * desc.k;
}
float ret = linear;
ret = powf(ret, 1.0f / desc.g);
ret *= desc.a;
ret -= (desc.a - 1);
return ret;
}
float LinearFromTf(const PiecewiseGammaDesc& desc, const float tf) {
const auto linear_if_low = tf / desc.k;
if (linear_if_low < desc.b) {
return linear_if_low;
}
float ret = tf;
ret += (desc.a - 1);
ret /= desc.a;
ret = powf(ret, 1.0f * desc.g);
return ret;
}
// -
mat3 YuvFromRgb(const YuvLumaCoeffs& yc) {
// Y is always [0,1]
// U and V are signed, and could be either [-1,+1] or [-0.5,+0.5].
// Specs generally use [-0.5,+0.5], so we use that too.
// E.g.
// y = 0.2126*r + 0.7152*g + 0.0722*b
// u = (b - y) / (u_range = u_max - u_min) // u_min = -u_max
// = (b - y) / (u(0,0,1) - u(1,1,0))
// = (b - y) / (2 * u(0,0,1))
// = (b - y) / (2 * u.b))
// = (b - y) / (2 * (1 - 0.0722))
// = (-0.2126*r + -0.7152*g + (1-0.0722)*b) / 1.8556
// v = (r - y) / 1.5748;
// = ((1-0.2126)*r + -0.7152*g + -0.0722*b) / 1.5748
const auto y = vec3({yc.r, yc.g, yc.b});
const auto u = vec3({0, 0, 1}) - y;
const auto v = vec3({1, 0, 0}) - y;
// From rows:
return mat3({y, u / (2 * u.z()), v / (2 * v.x())});
}
mat4 YuvFromYcbcr(const YcbcrDesc& d) {
// E.g.
// y = (yy - 16) / (235 - 16); // 16->0, 235->1
// u = (cb - 128) / (240 - 16); // 16->-0.5, 128->0, 240->+0.5
// v = (cr - 128) / (240 - 16);
const auto yRange = d.y1 - d.y0;
const auto uHalfRange = d.uPlusHalf - d.u0;
const auto uRange = 2 * uHalfRange;
const auto ycbcrFromYuv = mat4{{vec4{{yRange, 0, 0, d.y0}},
{{0, uRange, 0, d.u0}},
{{0, 0, uRange, d.u0}},
{{0, 0, 0, 1}}}};
const auto yuvFromYcbcr = inverse(ycbcrFromYuv);
return yuvFromYcbcr;
}
inline vec3 CIEXYZ_from_CIExyY(const vec2 xy, const float Y = 1) {
const auto xyz = vec3(xy, 1 - xy.x() - xy.y());
const auto XYZ = xyz * (Y / xy.y());
return XYZ;
}
mat3 XyzFromLinearRgb(const Chromaticities& c) {
// Given red (xr, yr), green (xg, yg), blue (xb, yb),
// and whitepoint (XW, YW, ZW)
// [ X ] [ R ]
// [ Y ] = M x [ G ]
// [ Z ] [ B ]
// [ Sr*Xr Sg*Xg Sb*Xb ]
// M = [ Sr*Yr Sg*Yg Sb*Yb ]
// [ Sr*Zr Sg*Zg Sb*Zb ]
// Xr = xr / yr
// Yr = 1
// Zr = (1 - xr - yr) / yr
// Xg = xg / yg
// Yg = 1
// Zg = (1 - xg - yg) / yg
// Xb = xb / yb
// Yb = 1
// Zb = (1 - xb - yb) / yb
// [ Sr ] [ Xr Xg Xb ]^-1 [ XW ]
// [ Sg ] = [ Yr Yg Yb ] x [ YW ]
// [ Sb ] [ Zr Zg Zb ] [ ZW ]
const auto xrgb = vec3({c.rx, c.gx, c.bx});
const auto yrgb = vec3({c.ry, c.gy, c.by});
const auto Xrgb = xrgb / yrgb;
const auto Yrgb = vec3(1);
const auto Zrgb = (vec3(1) - xrgb - yrgb) / yrgb;
const auto XYZrgb = mat3({Xrgb, Yrgb, Zrgb});
const auto XYZrgb_inv = inverse(XYZrgb);
const auto XYZwhitepoint = vec3({c.wx, c.wy, 1 - c.wx - c.wy}) / c.wy;
const auto Srgb = XYZrgb_inv * XYZwhitepoint;
const auto M = mat3({Srgb * Xrgb, Srgb * Yrgb, Srgb * Zrgb});
return M;
}
// -
ColorspaceTransform ColorspaceTransform::Create(const ColorspaceDesc& src,
const ColorspaceDesc& dst) {
auto ct = ColorspaceTransform{src, dst};
ct.srcTf = src.tf;
ct.dstTf = dst.tf;
const auto RgbTfFrom = [&](const ColorspaceDesc& cs) {
auto rgbFrom = mat4::Identity();
if (cs.yuv) {
const auto yuvFromYcbcr = YuvFromYcbcr(cs.yuv->ycbcr);
const auto yuvFromRgb = YuvFromRgb(cs.yuv->yCoeffs);
const auto rgbFromYuv = inverse(yuvFromRgb);
const auto rgbFromYuv4 = mat4(rgbFromYuv);
const auto rgbFromYcbcr = rgbFromYuv4 * yuvFromYcbcr;
rgbFrom = rgbFromYcbcr;
}
return rgbFrom;
};
ct.srcRgbTfFromSrc = RgbTfFrom(src);
const auto dstRgbTfFromDst = RgbTfFrom(dst);
ct.dstFromDstRgbTf = inverse(dstRgbTfFromDst);
// -
ct.dstRgbLinFromSrcRgbLin = mat3::Identity();
if (!(src.chrom == dst.chrom)) {
const auto xyzFromSrcRgbLin = XyzFromLinearRgb(src.chrom);
const auto xyzFromDstRgbLin = XyzFromLinearRgb(dst.chrom);
const auto dstRgbLinFromXyz = inverse(xyzFromDstRgbLin);
ct.dstRgbLinFromSrcRgbLin = dstRgbLinFromXyz * xyzFromSrcRgbLin;
}
return ct;
}
vec3 ColorspaceTransform::DstFromSrc(const vec3 src) const {
const auto srcRgbTf = srcRgbTfFromSrc * vec4(src, 1);
auto srcRgbLin = srcRgbTf;
if (srcTf) {
srcRgbLin.x(LinearFromTf(*srcTf, srcRgbTf.x()));
srcRgbLin.y(LinearFromTf(*srcTf, srcRgbTf.y()));
srcRgbLin.z(LinearFromTf(*srcTf, srcRgbTf.z()));
}
const auto dstRgbLin = dstRgbLinFromSrcRgbLin * vec3(srcRgbLin);
auto dstRgbTf = dstRgbLin;
if (dstTf) {
dstRgbTf.x(TfFromLinear(*dstTf, dstRgbLin.x()));
dstRgbTf.y(TfFromLinear(*dstTf, dstRgbLin.y()));
dstRgbTf.z(TfFromLinear(*dstTf, dstRgbLin.z()));
}
const auto dst4 = dstFromDstRgbTf * vec4(dstRgbTf, 1);
return vec3(dst4);
}
// -
mat3 XyzAFromXyzB_BradfordLinear(const vec2 xyA, const vec2 xyB) {
// This is what ICC profiles use to do whitepoint transforms,
// because ICC also requires D50 for the Profile Connection Space.
// E.3 "Linearized Bradford transformation":
const auto M_BFD = mat3{{
vec3{{0.8951, 0.2664f, -0.1614f}},
vec3{{-0.7502f, 1.7135f, 0.0367f}},
vec3{{0.0389f, -0.0685f, 1.0296f}},
}};
// NB: They use rho/gamma/beta, but we'll use R/G/B here.
const auto XYZDst = CIEXYZ_from_CIExyY(xyA); // "XYZ_W", WP of PCS
const auto XYZSrc = CIEXYZ_from_CIExyY(xyB); // "XYZ_NAW", WP of src
const auto rgbSrc = M_BFD * XYZSrc; // "RGB_SRC"
const auto rgbDst = M_BFD * XYZDst; // "RGB_PCS"
const auto rgbDstOverSrc = rgbDst / rgbSrc;
const auto M_dstOverSrc = mat3::Scale(rgbDstOverSrc);
const auto M_adapt = inverse(M_BFD) * M_dstOverSrc * M_BFD;
return M_adapt;
}
std::optional<mat4> ColorspaceTransform::ToMat4() const {
mat4 fromSrc = srcRgbTfFromSrc;
if (srcTf) return {};
fromSrc = mat4(dstRgbLinFromSrcRgbLin) * fromSrc;
if (dstTf) return {};
fromSrc = dstFromDstRgbTf * fromSrc;
return fromSrc;
}
Lut3 ColorspaceTransform::ToLut3(const ivec3 size) const {
auto lut = Lut3::Create(size);
lut.SetMap([&](const vec3& srcVal) { return DstFromSrc(srcVal); });
return lut;
}
vec3 Lut3::Sample(const vec3 in01) const {
const auto coord = vec3(size - 1) * in01;
const auto p0 = floor(coord);
const auto dp = coord - p0;
const auto ip0 = ivec3(p0);
// Trilinear
const auto f000 = Fetch(ip0 + ivec3({0, 0, 0}));
const auto f100 = Fetch(ip0 + ivec3({1, 0, 0}));
const auto f010 = Fetch(ip0 + ivec3({0, 1, 0}));
const auto f110 = Fetch(ip0 + ivec3({1, 1, 0}));
const auto f001 = Fetch(ip0 + ivec3({0, 0, 1}));
const auto f101 = Fetch(ip0 + ivec3({1, 0, 1}));
const auto f011 = Fetch(ip0 + ivec3({0, 1, 1}));
const auto f111 = Fetch(ip0 + ivec3({1, 1, 1}));
const auto fx00 = mix(f000, f100, dp.x());
const auto fx10 = mix(f010, f110, dp.x());
const auto fx01 = mix(f001, f101, dp.x());
const auto fx11 = mix(f011, f111, dp.x());
const auto fxy0 = mix(fx00, fx10, dp.y());
const auto fxy1 = mix(fx01, fx11, dp.y());
const auto fxyz = mix(fxy0, fxy1, dp.z());
return fxyz;
}
// -
ColorProfileDesc ColorProfileDesc::From(const ColorspaceDesc& cspace) {
auto ret = ColorProfileDesc{};
if (cspace.yuv) {
const auto yuvFromYcbcr = YuvFromYcbcr(cspace.yuv->ycbcr);
const auto yuvFromRgb = YuvFromRgb(cspace.yuv->yCoeffs);
const auto rgbFromYuv = inverse(yuvFromRgb);
ret.rgbFromYcbcr = mat4(rgbFromYuv) * yuvFromYcbcr;
}
if (cspace.tf) {
const size_t tableSize = 256;
auto& tableR = ret.linearFromTf.r;
tableR.resize(tableSize);
for (size_t i = 0; i < tableR.size(); i++) {
const float tfVal = i / float(tableR.size() - 1);
const float linearVal = LinearFromTf(*cspace.tf, tfVal);
tableR[i] = linearVal;
}
ret.linearFromTf.g = tableR;
ret.linearFromTf.b = tableR;
}
ret.xyzd65FromLinearRgb = XyzFromLinearRgb(cspace.chrom);
return ret;
}
// -
template <class T>
constexpr inline T NewtonEstimateX(const T x1, const T y1, const T dydx,
const T y2 = 0) {
// Estimate x s.t. y=0
// y = y0 + x*dydx;
// y0 = y - x*dydx;
// y1 - x1*dydx = y2 - x2*dydx
// x2*dydx = y2 - y1 + x1*dydx
// x2 = (y2 - y1)/dydx + x1
return (y2 - y1) / dydx + x1;
}
float GuessGamma(const std::vector<float>& vals, float exp_guess) {
// Approximate (signed) error = 0.0.
constexpr float d_exp = 0.001;
constexpr float error_tolerance = 0.001;
struct Samples {
float y1, y2;
};
const auto Sample = [&](const float exp) {
int i = -1;
auto samples = Samples{};
for (const auto& expected : vals) {
i += 1;
const auto in = i / float(vals.size() - 1);
samples.y1 += powf(in, exp) - expected;
samples.y2 += powf(in, exp + d_exp) - expected;
}
samples.y1 /= vals.size(); // Normalize by val count.
samples.y2 /= vals.size();
return samples;
};
constexpr int MAX_ITERS = 10;
for (int i = 1;; i++) {
const auto err = Sample(exp_guess);
const auto derr = err.y2 - err.y1;
exp_guess = NewtonEstimateX(exp_guess, err.y1, derr / d_exp);
// Check if we were close before, because then this last round of estimation
// should get us pretty much right on it.
if (std::abs(err.y1) < error_tolerance) {
return exp_guess;
}
if (i >= MAX_ITERS) {
printf_stderr("GuessGamma() -> %f after %i iterations (avg err %f)\n",
exp_guess, i, err.y1);
MOZ_ASSERT(false, "GuessGamma failed.");
return exp_guess;
}
}
}
// -
ColorProfileDesc ColorProfileDesc::From(const qcms_profile& qcmsProfile) {
ColorProfileDesc ret;
qcms_profile_data data = {};
qcms_profile_get_data(&qcmsProfile, &data);
auto xyzd50FromLinearRgb = mat3{};
// X contributions from [R,G,B]
xyzd50FromLinearRgb.at(0, 0) = data.red_colorant_xyzd50[0];
xyzd50FromLinearRgb.at(1, 0) = data.green_colorant_xyzd50[0];
xyzd50FromLinearRgb.at(2, 0) = data.blue_colorant_xyzd50[0];
// Y contributions from [R,G,B]
xyzd50FromLinearRgb.at(0, 1) = data.red_colorant_xyzd50[1];
xyzd50FromLinearRgb.at(1, 1) = data.green_colorant_xyzd50[1];
xyzd50FromLinearRgb.at(2, 1) = data.blue_colorant_xyzd50[1];
// Z contributions from [R,G,B]
xyzd50FromLinearRgb.at(0, 2) = data.red_colorant_xyzd50[2];
xyzd50FromLinearRgb.at(1, 2) = data.green_colorant_xyzd50[2];
xyzd50FromLinearRgb.at(2, 2) = data.blue_colorant_xyzd50[2];
const auto d65FromD50 = XyzAFromXyzB_BradfordLinear(D65, D50);
ret.xyzd65FromLinearRgb = d65FromD50 * xyzd50FromLinearRgb;
// -
const auto Fn = [&](std::vector<float>* const linearFromTf,
int32_t claimed_samples,
const qcms_color_channel channel) {
if (claimed_samples == 0) return; // No tf.
if (claimed_samples == -1) {
claimed_samples = 4096; // Ask it to generate a bunch.
claimed_samples = 256; // Ask it to generate a bunch.
}
linearFromTf->resize(AssertedCast<size_t>(claimed_samples));
const auto begin = linearFromTf->data();
qcms_profile_get_lut(&qcmsProfile, channel, begin,
begin + linearFromTf->size());
};
Fn(&ret.linearFromTf.r, data.linear_from_trc_red_samples,
qcms_color_channel::Red);
Fn(&ret.linearFromTf.b, data.linear_from_trc_blue_samples,
qcms_color_channel::Blue);
Fn(&ret.linearFromTf.g, data.linear_from_trc_green_samples,
qcms_color_channel::Green);
// -
return ret;
}
// -
ColorProfileConversionDesc ColorProfileConversionDesc::From(
const FromDesc& desc) {
const auto dstLinearRgbFromXyzd65 = inverse(desc.dst.xyzd65FromLinearRgb);
auto ret = ColorProfileConversionDesc{
.srcRgbFromSrcYuv = desc.src.rgbFromYcbcr,
.srcLinearFromSrcTf = desc.src.linearFromTf,
.dstLinearFromSrcLinear =
dstLinearRgbFromXyzd65 * desc.src.xyzd65FromLinearRgb,
.dstTfFromDstLinear = {},
};
bool sameTF = true;
sameTF &= desc.src.linearFromTf.r == desc.dst.linearFromTf.r;
sameTF &= desc.src.linearFromTf.g == desc.dst.linearFromTf.g;
sameTF &= desc.src.linearFromTf.b == desc.dst.linearFromTf.b;
if (sameTF) {
ret.srcLinearFromSrcTf = {};
ret.dstTfFromDstLinear = {};
} else {
const auto Invert = [](const std::vector<float>& linearFromTf,
std::vector<float>* const tfFromLinear) {
const auto size = linearFromTf.size();
MOZ_ASSERT(size != 1); // Less than two is uninvertable.
if (size < 2) return;
(*tfFromLinear).resize(size);
InvertLut(linearFromTf, &*tfFromLinear);
};
Invert(desc.dst.linearFromTf.r, &ret.dstTfFromDstLinear.r);
Invert(desc.dst.linearFromTf.g, &ret.dstTfFromDstLinear.g);
Invert(desc.dst.linearFromTf.b, &ret.dstTfFromDstLinear.b);
}
return ret;
}
} // namespace mozilla::color