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authorPacien TRAN-GIRARD2015-12-08 11:32:48 +0100
committerPacien TRAN-GIRARD2015-12-08 11:32:48 +0100
commit26d6f24e97583e033c79d8df84b199748fcaa436 (patch)
tree6b660f86e9ae8c48a15c7a40c71696cc7d1e95d6 /src
parenta98c2a7fe70640f3c855e6e13f664165b0a4e466 (diff)
downloadseam-stitcher-26d6f24e97583e033c79d8df84b199748fcaa436.tar.gz
Fix and simplify filter convolutionHEADmaster
Diffstat (limited to 'src')
-rw-r--r--src/main/java/Filter.java61
1 files changed, 29 insertions, 32 deletions
diff --git a/src/main/java/Filter.java b/src/main/java/Filter.java
index 7e55f04..d88ea07 100644
--- a/src/main/java/Filter.java
+++ b/src/main/java/Filter.java
@@ -42,6 +42,32 @@ public final class Filter {
42 } 42 }
43 43
44 /** 44 /**
45 * Combine neighbour pixels using the given kernel.
46 *
47 * @param gray a HxW float array
48 * @param kernel a MxN float array, with M and N odd
49 * @param row Y coordinate
50 * @param col X coordinate
51 * @return the pixel value
52 */
53 private static float combineNeighbours(float[][] gray, float[][] kernel, int row, int col) {
54 int kernelWidth = kernel[0].length;
55 int kernelHeight = kernel.length;
56
57 int rowOffset = row - kernelWidth / 2; // int division
58 int colOffset = col - kernelHeight / 2; // int division
59
60 float pixelValue = 0;
61
62 for (int kernelRow = 0; kernelRow < kernelHeight; ++kernelRow)
63 for (int kernelCol = 0; kernelCol < kernelWidth; ++kernelCol)
64 pixelValue += kernel[kernelRow][kernelCol]
65 * Filter.at(gray, rowOffset + kernelRow, colOffset + kernelCol);
66
67 return pixelValue;
68 }
69
70 /**
45 * Convolve a single-channel image with specified kernel. 71 * Convolve a single-channel image with specified kernel.
46 * 72 *
47 * @param gray a HxW float array 73 * @param gray a HxW float array
@@ -52,40 +78,11 @@ public final class Filter {
52 int width = gray[0].length; 78 int width = gray[0].length;
53 int height = gray.length; 79 int height = gray.length;
54 80
55 int kernelWidth = kernel[0].length;
56 int kernelHeight = kernel.length;
57
58 float pixelNeighbors[][] = new float[kernelHeight][kernelWidth];
59 float[][] filteredImage = new float[height][width]; 81 float[][] filteredImage = new float[height][width];
60 82
61 for (int row = 0; row < height; ++row) { 83 for (int row = 0; row < height; ++row)
62 for (int col = 0; col < width; ++col) { 84 for (int col = 0; col < width; ++col)
63 85 filteredImage[row][col] = Filter.combineNeighbours(gray, kernel, row, col);
64 int pixelRow = -kernelHeight / 2;
65 int pixelCol = -kernelWidth / 2;
66
67 for (int kernelRow = 0; kernelRow < kernelWidth; kernelRow++) {
68 for (int kernelCol = 0; kernelCol < kernelHeight; kernelCol++) {
69 pixelNeighbors[kernelRow][kernelCol] = Filter.at(gray, row + pixelRow, col + pixelCol);
70
71 pixelCol += 1;
72 if (pixelCol > kernelWidth / 2) {
73 pixelCol = -kernelWidth / 2;
74 }
75 }
76 pixelRow += 1;
77 if (pixelRow > kernelHeight / 2) {
78 pixelRow = -kernelHeight / 2;
79 }
80 }
81
82 for (int i = 0; i < kernelWidth; i++) {
83 for (int j = 0; j < kernelHeight; j++) {
84 filteredImage[row][col] += kernel[i][j] * pixelNeighbors[i][j];
85 }
86 }
87 }
88 }
89 86
90 return filteredImage; 87 return filteredImage;
91 } 88 }