I wanted to do a regression on a set of data A(k1,k2), however I wanted limit it regression within a range of -K1<k1<K1 and -K2<k<K2. A is an image phase consist of 60x60 matrix, with dimension of MxN. Least squares approximation to be done by 0.1N/2 from the center of normalized frequency area of A.
Here's the portion of the code:
A=rand(60);
[m, n]=size(A);
[M,N] = meshgrid(1:m,1:n);
X = [M(:), N(:)];
B=regress(A(:), X); %regression will be done on all the values of A, part where adjustment needed
hat=reshape(X*B,m,n);
You can first select the subset of your matrix on which you want to perform the regression:
% generate the full image
A_full=rand(60);
[m, n]=size(A_full);
% select the part you want,
% it is not very clear to me if this is really the part you want,
% but I think you will be able to change it to your needs
A=A_full(floor(m/2-0.1*m/2):ceil(m/2+0.1*m/2), floor(n/2-0.1*n/2):ceil(n/2+0.1*n/2));
% perform the regression on the selected part of A (like you did it)
[m, n]=size(A);
[M,N] = meshgrid(1:m,1:n);
X = [M(:), N(:)];
B=regress(A(:), X); %regression will be done on all the values of A, part where adjustment needed
hat=reshape(X*B,m,n);