Constrained least squares filter (CLS) Filter

The main goal of this project is to apply signals and systems to filter 2-D signals.

a constrained least squares filter based on the explanations below and apply it to the image in the "noisy_blur_img.mat"

F(u, v) = the reconstructed image spectrum,

G(u, v) = the degraded image spectrum,

H(u, v) = the degradation function,

H*(u, v) = the complex conjugate of H(u,v),

|H(u, v)|^2= H*(u, v)H(u, v), and

P(u, v) = the spectrum of the Laplacian kernel. The Laplacian kernel p(x, y) is equal to [0 -1 0; -1 4 -1, 0 -1 0]