Reland "use linear segment instead of recalculating it"
This is a reland of 86807d30cc2951021e81dc4507a5c14b37aebd31
Original change's description:
> use linear segment instead of recalculating it
>
> Change-Id: I55f8e5d23f7f77681f45cfe2255ef8dda416497f
> Reviewed-on: https://skia-review.googlesource.com/123583
> Reviewed-by: Brian Osman <brianosman@google.com>
> Commit-Queue: Brian Osman <brianosman@google.com>
> Commit-Queue: Mike Klein <mtklein@google.com>
> Auto-Submit: Mike Klein <mtklein@chromium.org>
Change-Id: I3b98c03923b811499bec4e337a45a1937b547538
Reviewed-on: https://skia-review.googlesource.com/123682
Commit-Queue: Mike Klein <mtklein@google.com>
Reviewed-by: Mike Klein <mtklein@google.com>
diff --git a/profiles/misc/MartiMaria_browsertest_HARD.icc.txt b/profiles/misc/MartiMaria_browsertest_HARD.icc.txt
index 46b4cf2..38fdd04 100644
--- a/profiles/misc/MartiMaria_browsertest_HARD.icc.txt
+++ b/profiles/misc/MartiMaria_browsertest_HARD.icc.txt
@@ -49,4 +49,4 @@
7b8069 7b8069 7b8069 7b8069 7b8069 7b8069 7b8069
7b8069 7b8069 7b8069 7b8069 7b8069 060605 7b8069
7b8069 7b8069 7b8069 7b8069 686c59 7b8069 7b8069
-polyTF[1] = 0 0 0.003876 1
+polyTF[1] = 0 0 0.003876 inf
diff --git a/profiles/misc/sRGB_lcms.icc.txt b/profiles/misc/sRGB_lcms.icc.txt
index 7030fb2..591b2f0 100644
--- a/profiles/misc/sRGB_lcms.icc.txt
+++ b/profiles/misc/sRGB_lcms.icc.txt
@@ -38,6 +38,6 @@
2a4215 322481 110a31 582e06 599714 03020c 4f59a4
63a91b 43292c 394539 5c3b22 548d3f 4d3018 506084
This profile ≈ sRGB.
-polyTF[0] = 0.2941 0.7039 0.07759 0.04314
-polyTF[1] = 0.2941 0.7039 0.07759 0.04314
-polyTF[2] = 0.2941 0.7039 0.07759 0.04314
+polyTF[0] = 0.2938 0.7042 0.07739 0.04045
+polyTF[1] = 0.2938 0.7042 0.07739 0.04045
+polyTF[2] = 0.2938 0.7042 0.07739 0.04045
diff --git a/profiles/mobile/Display_P3_parametric.icc.txt b/profiles/mobile/Display_P3_parametric.icc.txt
index 865645a..8916828 100644
--- a/profiles/mobile/Display_P3_parametric.icc.txt
+++ b/profiles/mobile/Display_P3_parametric.icc.txt
@@ -37,6 +37,6 @@
6c616e 5f3a66 2e5e07 5e2b62 371928 293053 5a6591
234012 34258c 120a35 673203 499209 03020d 4b58ad
4fa40f 4d2b2d 364439 683e21 448939 573317 4b5e8a
-polyTF[0] = 0.2941 0.7039 0.07759 0.04314
-polyTF[1] = 0.2941 0.7039 0.07759 0.04314
-polyTF[2] = 0.2941 0.7039 0.07759 0.04314
+polyTF[0] = 0.2938 0.7042 0.07739 0.04045
+polyTF[1] = 0.2938 0.7042 0.07739 0.04045
+polyTF[2] = 0.2938 0.7042 0.07739 0.04045
diff --git a/profiles/mobile/iPhone7p.icc.txt b/profiles/mobile/iPhone7p.icc.txt
index 80366bc..bb59c5e 100644
--- a/profiles/mobile/iPhone7p.icc.txt
+++ b/profiles/mobile/iPhone7p.icc.txt
@@ -36,6 +36,6 @@
6c616e 5f3a65 2d5e07 5e2b62 371928 293053 5a6591
234012 34258c 120a35 673203 499209 03020d 4b58ad
4fa40f 4d2b2d 364439 683e21 448939 573317 4b5e8a
-polyTF[0] = 0.2945 0.7035 0.07733 0.04314
-polyTF[1] = 0.2945 0.7035 0.07733 0.04314
-polyTF[2] = 0.2945 0.7035 0.07733 0.04314
+polyTF[0] = 0.2941 0.704 0.077 0.039
+polyTF[1] = 0.2941 0.704 0.077 0.039
+polyTF[2] = 0.2941 0.704 0.077 0.039
diff --git a/profiles/mobile/sRGB_parametric.icc.txt b/profiles/mobile/sRGB_parametric.icc.txt
index 04c70cc..05bed41 100644
--- a/profiles/mobile/sRGB_parametric.icc.txt
+++ b/profiles/mobile/sRGB_parametric.icc.txt
@@ -38,6 +38,6 @@
2a4215 322481 110a31 582e06 599714 03020c 4f59a4
63a91b 43292c 394539 5c3b22 548d3f 4d3018 506084
This profile ≈ sRGB.
-polyTF[0] = 0.2941 0.7039 0.07759 0.04314
-polyTF[1] = 0.2941 0.7039 0.07759 0.04314
-polyTF[2] = 0.2941 0.7039 0.07759 0.04314
+polyTF[0] = 0.2938 0.7042 0.07739 0.04045
+polyTF[1] = 0.2938 0.7042 0.07739 0.04045
+polyTF[2] = 0.2938 0.7042 0.07739 0.04045
diff --git a/src/PolyTF.c b/src/PolyTF.c
index f4aaa48..f4d837b 100644
--- a/src/PolyTF.c
+++ b/src/PolyTF.c
@@ -67,7 +67,7 @@
}
const int N = curve->table_entries == 0 ? 256
- :(int)curve->table_entries;
+ : (int)curve->table_entries;
// We'll test the quality of our fit by roundtripping through a skcms_TransferFunction,
// either the inverse of the curve itself if it is parametric, or of its approximation if not.
@@ -78,64 +78,74 @@
} else if (!skcms_ApproximateCurve(curve, &baseline, &err)) {
return false;
}
+
+ // We'll borrow the linear section from baseline, which is either
+ // exactly correct, or already the approximation we'd use anyway.
+ tf->C = baseline.c;
+ tf->D = baseline.d;
+ if (baseline.f != 0) {
+ return false; // Can't fit this (rare) kind of curve here.
+ }
+
+ // Detect linear baseline: (ax + b)^g + e --> ax ~~> Cx
+ if (baseline.g == 1 && baseline.d == 0 && baseline.b + baseline.e == 0) {
+ tf->A = 0;
+ tf->B = 0;
+ tf->C = baseline.a;
+ tf->D = INFINITY_; // Always use Cx, never Ax^3+Bx^2+(1-A-B)
+ return true;
+ }
+ // This case is less likely, but also guards against divide by zero below.
+ if (tf->D == 1) {
+ tf->A = 0;
+ tf->B = 0;
+ return true;
+ }
+
+ // Number of points already fit in the linear section.
+ // If the curve isn't parametric and we approximated instead, this should be exact.
+ const int L = (int)(tf->D * (N-1)) + 1;
+
+ // TODO: handle special case of L == N-1 to avoid /0 in Gauss-Newton.
+
skcms_TransferFunction inv;
if (!skcms_TransferFunction_invert(&baseline, &inv)) {
return false;
}
- const float kTolerances[] = { 1.5f / 65535.0f, 1.0f / 512.0f };
- for (int t = 0; t < ARRAY_COUNT(kTolerances); t++) {
- float f;
- const int L = skcms_fit_linear(curve, N, kTolerances[t], &tf->C, &tf->D, &f);
- if (f != 0) {
+ // Start with guess A = 0, i.e. f(x) ≈ x^2.
+ float P[4] = {0, 0,0,0};
+ for (int i = 0; i < 3; i++) {
+ if (!skcms_gauss_newton_step(skcms_eval_curve, curve,
+ eval_poly_tf, tf,
+ grad_poly_tf, tf,
+ P,
+ tf->D, 1, N-L)) {
+ return false;
+ }
+ }
+
+ float A = tf->A = P[0],
+ C = tf->C,
+ D = tf->D;
+ tf->B = (C*D - A*(D*D*D - 1) - 1) / (D*D - 1);
+
+ for (int i = 0; i < N; i++) {
+ float x = i * (1.0f/(N-1));
+
+ float rt = skcms_TransferFunction_eval(&inv, eval_poly_tf(x, tf, P));
+ if (!isfinitef_(rt)) {
return false;
}
- if (tf->D == 1) {
- tf->A = 0;
- tf->B = 0;
- return true;
+ const int tol = (i == 0 || i == N-1) ? 0
+ : N/256;
+ int ix = (int)((N-1) * rt + 0.5f);
+ if (abs(i - ix) > tol) {
+ return false;
}
-
- // Start with guess A = 0, i.e. f(x) = x^2, gamma = 2.
- float P[4] = {0, 0,0,0};
-
- for (int i = 0; i < 3; i++) {
- if (!skcms_gauss_newton_step(skcms_eval_curve, curve,
- eval_poly_tf, tf,
- grad_poly_tf, tf,
- P,
- tf->D, 1, N-L)) {
- goto NEXT;
- }
- }
-
- float A = tf->A = P[0],
- C = tf->C,
- D = tf->D;
- tf->B = (C*D - A*(D*D*D - 1) - 1) / (D*D - 1);
-
- for (int i = 0; i < N; i++) {
- float x = i * (1.0f/(N-1));
-
- float rt = skcms_TransferFunction_eval(&inv, eval_poly_tf(x, tf, P));
- if (!isfinitef_(rt)) {
- goto NEXT;
- }
-
- const int tol = (i == 0 || i == N-1) ? 0
- : N/256;
- int ix = (int)((N-1) * rt + 0.5f);
- if (abs(i - ix) > tol) {
- goto NEXT;
- }
- }
- return true;
-
- NEXT: ;
}
-
- return false;
+ return true;
}
void skcms_OptimizeForSpeed(skcms_ICCProfile* profile) {
