1 /*
2 * Copyright 2016 Google Inc.
3 *
4 * Use of this source code is governed by a BSD-style license that can be
5 * found in the LICENSE file.
6 */
7
8 #include "SkColorLookUpTable.h"
9 #include "SkColorSpaceXformPriv.h"
10 #include "SkFloatingPoint.h"
11
interp(float * dst,const float * src) const12 void SkColorLookUpTable::interp(float* dst, const float* src) const {
13 if (fInputChannels == 3) {
14 interp3D(dst, src);
15 } else {
16 SkASSERT(dst != src);
17 // index gets initialized as the algorithm proceeds by interpDimension.
18 // It's just there to store the choice of low/high so far.
19 int index[kMaxColorChannels];
20 for (uint8_t outputDimension = 0; outputDimension < kOutputChannels; ++outputDimension) {
21 dst[outputDimension] = interpDimension(src, fInputChannels - 1, outputDimension,
22 index);
23 }
24 }
25 }
26
interp3D(float * dst,const float * src) const27 void SkColorLookUpTable::interp3D(float* dst, const float* src) const {
28 SkASSERT(3 == kOutputChannels);
29 // Call the src components x, y, and z.
30 const uint8_t maxX = fGridPoints[0] - 1;
31 const uint8_t maxY = fGridPoints[1] - 1;
32 const uint8_t maxZ = fGridPoints[2] - 1;
33
34 // An approximate index into each of the three dimensions of the table.
35 const float x = src[0] * maxX;
36 const float y = src[1] * maxY;
37 const float z = src[2] * maxZ;
38
39 // This gives us the low index for our interpolation.
40 int ix = sk_float_floor2int(x);
41 int iy = sk_float_floor2int(y);
42 int iz = sk_float_floor2int(z);
43
44 // Make sure the low index is not also the max index.
45 ix = (maxX == ix) ? ix - 1 : ix;
46 iy = (maxY == iy) ? iy - 1 : iy;
47 iz = (maxZ == iz) ? iz - 1 : iz;
48
49 // Weighting factors for the interpolation.
50 const float diffX = x - ix;
51 const float diffY = y - iy;
52 const float diffZ = z - iz;
53
54 // Constants to help us navigate the 3D table.
55 // Ex: Assume x = a, y = b, z = c.
56 // table[a * n001 + b * n010 + c * n100] logically equals table[a][b][c].
57 const int n000 = 0;
58 const int n001 = 3 * fGridPoints[1] * fGridPoints[2];
59 const int n010 = 3 * fGridPoints[2];
60 const int n011 = n001 + n010;
61 const int n100 = 3;
62 const int n101 = n100 + n001;
63 const int n110 = n100 + n010;
64 const int n111 = n110 + n001;
65
66 // Base ptr into the table.
67 const float* ptr = &(table()[ix*n001 + iy*n010 + iz*n100]);
68
69 // The code below performs a tetrahedral interpolation for each of the three
70 // dst components. Once the tetrahedron containing the interpolation point is
71 // identified, the interpolation is a weighted sum of grid values at the
72 // vertices of the tetrahedron. The claim is that tetrahedral interpolation
73 // provides a more accurate color conversion.
74 // blogs.mathworks.com/steve/2006/11/24/tetrahedral-interpolation-for-colorspace-conversion/
75 //
76 // I have one test image, and visually I can't tell the difference between
77 // tetrahedral and trilinear interpolation. In terms of computation, the
78 // tetrahedral code requires more branches but less computation. The
79 // SampleICC library provides an option for the client to choose either
80 // tetrahedral or trilinear.
81 for (int i = 0; i < 3; i++) {
82 if (diffZ < diffY) {
83 if (diffZ > diffX) {
84 dst[i] = (ptr[n000] + diffZ * (ptr[n110] - ptr[n010]) +
85 diffY * (ptr[n010] - ptr[n000]) +
86 diffX * (ptr[n111] - ptr[n110]));
87 } else if (diffY < diffX) {
88 dst[i] = (ptr[n000] + diffZ * (ptr[n111] - ptr[n011]) +
89 diffY * (ptr[n011] - ptr[n001]) +
90 diffX * (ptr[n001] - ptr[n000]));
91 } else {
92 dst[i] = (ptr[n000] + diffZ * (ptr[n111] - ptr[n011]) +
93 diffY * (ptr[n010] - ptr[n000]) +
94 diffX * (ptr[n011] - ptr[n010]));
95 }
96 } else {
97 if (diffZ < diffX) {
98 dst[i] = (ptr[n000] + diffZ * (ptr[n101] - ptr[n001]) +
99 diffY * (ptr[n111] - ptr[n101]) +
100 diffX * (ptr[n001] - ptr[n000]));
101 } else if (diffY < diffX) {
102 dst[i] = (ptr[n000] + diffZ * (ptr[n100] - ptr[n000]) +
103 diffY * (ptr[n111] - ptr[n101]) +
104 diffX * (ptr[n101] - ptr[n100]));
105 } else {
106 dst[i] = (ptr[n000] + diffZ * (ptr[n100] - ptr[n000]) +
107 diffY * (ptr[n110] - ptr[n100]) +
108 diffX * (ptr[n111] - ptr[n110]));
109 }
110 }
111
112 // |src| is guaranteed to be in the 0-1 range as are all entries
113 // in the table. For "increasing" tables, outputs will also be
114 // in the 0-1 range. While this property is logical for color
115 // look up tables, we don't check for it.
116 // And for arbitrary, non-increasing tables, it is easy to see how
117 // the output might not be 0-1. So we clamp here.
118 dst[i] = clamp_0_1(dst[i]);
119
120 // Increment the table ptr in order to handle the next component.
121 // Note that this is the how table is designed: all of nXXX
122 // variables are multiples of 3 because there are 3 output
123 // components.
124 ptr++;
125 }
126 }
127
interpDimension(const float * src,int inputDimension,int outputDimension,int index[kMaxColorChannels]) const128 float SkColorLookUpTable::interpDimension(const float* src, int inputDimension,
129 int outputDimension,
130 int index[kMaxColorChannels]) const {
131 // Base case. We've already decided whether to use the low or high point for each dimension
132 // which is stored inside of index[] where index[i] gives the point in the CLUT to use for
133 // input dimension i.
134 if (inputDimension < 0) {
135 // compute index into CLUT and look up the colour
136 int outputIndex = outputDimension;
137 int indexMultiplier = kOutputChannels;
138 for (int i = fInputChannels - 1; i >= 0; --i) {
139 outputIndex += index[i] * indexMultiplier;
140 indexMultiplier *= fGridPoints[i];
141 }
142 return table()[outputIndex];
143 }
144 // for each dimension (input channel), try both the low and high point for it
145 // and then do the same recursively for the later dimensions.
146 // Finally, we need to LERP the results. ie LERP X then LERP Y then LERP Z.
147 const float x = src[inputDimension] * (fGridPoints[inputDimension] - 1);
148 // try the low point for this dimension
149 index[inputDimension] = sk_float_floor2int(x);
150 const float diff = x - index[inputDimension];
151 // and recursively LERP all sub-dimensions with the current dimension fixed to the low point
152 const float lo = interpDimension(src, inputDimension - 1, outputDimension, index);
153 // now try the high point for this dimension
154 index[inputDimension] = sk_float_ceil2int(x);
155 // and recursively LERP all sub-dimensions with the current dimension fixed to the high point
156 const float hi = interpDimension(src, inputDimension - 1, outputDimension, index);
157 // then LERP the results based on the current dimension
158 return clamp_0_1((1 - diff) * lo + diff * hi);
159 }
160