Image processing: Interative optimization problem by a gradient descent approach
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I have to find the image X that minimizes the following cost function:
f=||A-(abs(X).^2-conj(X).*B)||^2
where:
- A, B and X are MxN matrices
- A and B are known images
- || is the usual norm operator
The problem has to be solved iteratively using a gradient (respect to conj(X)) descent approach. The gradient respect to conj(X) is:
g=-2*(A-(abs(X).^2-conj(X).*B))(X+B)
I'm absolutely blocked, I will be very grateful for any help provided.
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asim asrar
il 2 Feb 2022
Dear sir,
Did you get any clue to solve this problem, as i am also struck with similar type of problem.
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