skcms→91a8958 Detect and canonicalize identity tables

Change-Id: I36957b8d7d96ac262b509c218779775c90864314
Reviewed-on: https://skia-review.googlesource.com/120420
Reviewed-by: Mike Klein <mtklein@chromium.org>
Commit-Queue: Mike Klein <mtklein@chromium.org>

3 files changed, 50 insertions, 10 deletions

diff --git a/third_party/skcms/src/ICCProfile.c b/third_party/skcms/src/ICCProfile.c
index 9c504cd3ce..a21abd0041 100644
--- a/third_party/skcms/src/ICCProfile.c
+++ b/third_party/skcms/src/ICCProfile.c
@@ -226,7 +226,7 @@ static bool read_curve_curv(const uint8_t* buf, uint32_t size,
         curve->parametric.e  = 0.0f;
         curve->parametric.f  = 0.0f;
         if (value_count == 0) {
-            // Empty tables are a shorthand for linear
+            // Empty tables are a shorthand for an identity curve
             curve->parametric.g = 1.0f;
         } else {
             // Single entry tables are a shorthand for simple gamma
@@ -581,15 +581,51 @@ static bool read_tag_mab(const skcms_ICCTag* tag, skcms_A2B* a2b, bool pcs_is_xy
 }
 
 static bool read_a2b(const skcms_ICCTag* tag, skcms_A2B* a2b, bool pcs_is_xyz) {
+    bool ok = false;
     if (tag->type == make_signature('m', 'f', 't', '1')) {
-        return read_tag_mft1(tag, a2b);
+        ok = read_tag_mft1(tag, a2b);
     } else if (tag->type == make_signature('m', 'f', 't', '2')) {
-        return read_tag_mft2(tag, a2b);
+        ok = read_tag_mft2(tag, a2b);
     } else if (tag->type == make_signature('m', 'A', 'B', ' ')) {
-        return read_tag_mab(tag, a2b, pcs_is_xyz);
+        ok = read_tag_mab(tag, a2b, pcs_is_xyz);
+    }
+    if (!ok) {
+        return false;
     }
 
-    return false;
+    // Detect and canonicalize identity tables.
+    skcms_Curve* curves[] = {
+        a2b->input_channels  > 0 ? a2b->input_curves  + 0 : NULL,
+        a2b->input_channels  > 1 ? a2b->input_curves  + 1 : NULL,
+        a2b->input_channels  > 2 ? a2b->input_curves  + 2 : NULL,
+        a2b->input_channels  > 3 ? a2b->input_curves  + 3 : NULL,
+        a2b->matrix_channels > 0 ? a2b->matrix_curves + 0 : NULL,
+        a2b->matrix_channels > 1 ? a2b->matrix_curves + 1 : NULL,
+        a2b->matrix_channels > 2 ? a2b->matrix_curves + 2 : NULL,
+        a2b->output_channels > 0 ? a2b->output_curves + 0 : NULL,
+        a2b->output_channels > 1 ? a2b->output_curves + 1 : NULL,
+        a2b->output_channels > 2 ? a2b->output_curves + 2 : NULL,
+    };
+
+    for (int i = 0; i < ARRAY_COUNT(curves); i++) {
+        skcms_Curve* curve = curves[i];
+
+        if (curve && curve->table_entries && curve->table_entries <= (uint32_t)INT_MAX) {
+            int N = (int)curve->table_entries;
+
+            skcms_TransferFunction tf;
+            if (N == skcms_fit_linear(curve, N, 1.0f/(2*N), &tf)
+                && tf.c == 1.0f
+                && tf.f == 0.0f) {
+                curve->table_entries = 0;
+                curve->table_8       = NULL;
+                curve->table_16      = NULL;
+                curve->parametric    = (skcms_TransferFunction){1,1,0,0,0,0,0};
+            }
+        }
+    }
+
+    return true;
 }
 
 void skcms_GetTagByIndex(const skcms_ICCProfile* profile, uint32_t idx, skcms_ICCTag* tag) {
diff --git a/third_party/skcms/src/TransferFunction.c b/third_party/skcms/src/TransferFunction.c
index 6ddc9772d0..56245ad6d0 100644
--- a/third_party/skcms/src/TransferFunction.c
+++ b/third_party/skcms/src/TransferFunction.c
@@ -116,8 +116,8 @@ bool skcms_TransferFunction_invert(const skcms_TransferFunction* src, skcms_Tran
 //
 // Our overall strategy is then:
 //    For a couple tolerances,
-//       - fit_linear():     fit c,d,f iteratively to as many points as our tolerance allows
-//       - fit_nonlinear():  fit g,a,b using Gauss-Newton given c,d,f (and by constraint, e)
+//       - skcms_fit_linear(): fit c,d,f iteratively to as many points as our tolerance allows
+//       - fit_nonlinear():    fit g,a,b using Gauss-Newton given c,d,f (and by constraint, e)
 //    Return the parameters with least maximum error.
 //
 // To run Gauss-Newton to find g,a,b, we'll also need the gradient of the non-linear piece:
@@ -161,8 +161,8 @@ static void grad_nonlinear(float x, const void* ctx, const float P[4], float dfd
             -   g*powf_(D, g-1);
 }
 
-// Returns the number of points that are approximated by the line, to within tol.
-static int fit_linear(const skcms_Curve* curve, int N, float tol, skcms_TransferFunction* tf) {
+int skcms_fit_linear(const skcms_Curve* curve, int N, float tol, skcms_TransferFunction* tf) {
+    assert(N > 1);
     // We iteratively fit the first points to the TF's linear piece.
     // We want the cx + f line to pass through the first and last points we fit exactly.
     //
@@ -267,7 +267,7 @@ bool skcms_ApproximateCurve(const skcms_Curve* curve,
     const float kTolerances[] = { 1.5f / 65535.0f, 1.0f / 512.0f };
     for (int t = 0; t < ARRAY_COUNT(kTolerances); t++) {
         skcms_TransferFunction tf;
-        int L = fit_linear(curve, N, kTolerances[t], &tf);
+        int L = skcms_fit_linear(curve, N, kTolerances[t], &tf);
 
         if (L == N) {
             // If the entire data set was linear, move the coefficients to the nonlinear portion
diff --git a/third_party/skcms/src/TransferFunction.h b/third_party/skcms/src/TransferFunction.h
index c98c78d7e7..284b1364ed 100644
--- a/third_party/skcms/src/TransferFunction.h
+++ b/third_party/skcms/src/TransferFunction.h
@@ -14,3 +14,7 @@
 float skcms_TransferFunction_eval(const skcms_TransferFunction*, float);
 
 bool skcms_TransferFunction_invert(const skcms_TransferFunction*, skcms_TransferFunction*);
+
+// Fit c,d,f parameters of an skcms_TransferFunction to the first 2 < L ≤ N
+// evenly-spaced points on an skcms_Curve within a given tolerance, returning L.
+int skcms_fit_linear(const skcms_Curve*, int N, float tol, skcms_TransferFunction*);