Reputation: 5342
Can you please tell me how does the kernel of a 2D top hat filter looks like? I created the following kernel,
0 0 0 -1 0 0 0
0 -1 -1 -1 -1 -1 0
0 -1 -1 1 -1 -1 0
-1 -1 1 1 1 -1 -1
0 -1 -1 1 -1 -1 0
0 -1 -1 -1 -1 -1 0
0 0 0 -1 0 0 0
does this qualify as a top hat filter kernel? If I convolute an image with this matrix, is it equivalent to have done a top hat filtering operation? Am sorry if the question is rudimentary, but your help is much appreciated.
Upvotes: 0
Views: 2045
Reputation: 212979
Top hat is a very loose term which can mean different things in different contexts.
For spatial domain filtering a top hat filter generally has coefficients of 1 in the central area and 0 beyond this. However it is not a particularly useful filter as its frequency response is a sinc function.
More commonly "top hat" refers to a morphological operation in image processing used to extract small elements and details. This is quite different from the top hat spatial filter described above.
Upvotes: 1