Large-scale constrained linear least-squares optimization


Slide 2






Our starting image is the black and white image shown above, contained the m x n matrix P. Each element in the matrix represents a pixel's gray intensity between black and white (0 and 1).
>> [m,n]=size(P);
>> mn=m*n;
>> imagesc(P);
>> colormap(gray);
>> axis image; axis off;
>> title([num2str(m) ' x ' num2str(n) ' (' num2str(mn) ' pixels)']);