Hi Amjad,
There are many things, I don't understand in the code. First line defining the variable "img" seems odd because the way you defined it give the same of "img" as [ 1 ,6016] which I don't think is intended. May be that's the reason of you getting abrubt values in C. You can simply define the size of image in img and define C accordingly
img = [1664,4352] % Size of image.
C = zeros(img); % Define C according to the size of image.
Also, yes these can be optimized, I don't know what the doppler_centroid function do. But you can remove both the for loop and convert this problem in matrix space and then use a convolution filter to solve the problem, Refer conv2 function. I will give an example describing how it can be useful.
% Let try to find a simple mean of the sliding window.
A = rand(10,10);
B = ones(2,2)./4; % Design a matrix for taking average.
C = conv2(A,B,"same"); % This matrix is the result of average over a sliding window of length 2.
Do try out the above code and adapt in your case.
I hope this helps.
Cheers.
