In image processing, convolution matrix, or mask is a small matrix. It is used for blurring, sharpening, embossing, edge detection, and more.
Kernel:
0 | 0 | 0 |
0 | 1 | 0 |
0 | 0 | 0 |
Kernel:
0 | 1 | 0 |
1 | -4 | 1 |
0 | 1 | 0 |
Kernel:
0 | 0 | 0 | 0 | 0 |
0 | 0 | 5 | 0 | 0 |
0 | -1 | 5 | -1 | 0 |
0 | 0 | 1 | 0 | 0 |
0 | 0 | 0 | 0 | 0 |
Normalization rate = 16
Kernel:
1 | 2 | 1 |
2 | 4 | 2 |
1 | 2 | 1 |
Normalization rate = 256
Kernel:
1 | 4 | 6 | 4 | 1 |
4 | 16 | 24 | 16 | 4 |
6 | 24 | 36 | 24 | 6 |
4 | 16 | 24 | 16 | 4 |
1 | 4 | 6 | 4 | 1 |
Normalization rate = 9
Kernel:
1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |
0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 |
0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
Kernel:
-2 | -1 | 0 |
-1 | 1 | 1 |
0 | 1 | 2 |
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