I am interested to know, how a summation(Sigma) works if there are multi indexes under it? (Like what I have underlined by red in the following image)
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I am interested to know, how a summation(Sigma) works if there are multi indexes under it? (Like what I have underlined by red in the following image)
I am interested to know, how a summation(Sigma) works if there are multi indexes under it? (Like what I have underlined by red in the following image)
EDIT(add more information):
The denoising algorithm implemented in OpenCV is called Fast Non-Local Means Denoising (FNLMD), and is based on work by Antoni Buades, Bartomeu Coll, and Jean-Michel Morel
The identification of similar pixels proceeds based on a window B(p, s) centered on pixel p and of size s. Given such a window around the point we wish to update, we can compare that window with an analogous window around some other pixel q. We define the square distance between B(p, s) and B(q, s) to be:
Where c is the color index, I c (p) is the intensity of the image in channel c at point p, and the summation over j is over the elements of the patch. From this square dis‐ tance, a weight can be assigned to every other pixel relative to the pixel currently being updated.