Image Degradation And Restoration Model :- As fig. show, that degradation process is modeled as a degradation function that, together with an additive noise term, Operates on an input Image f(x,y), to produce a degraded image g(x,y), some knowledge about the degradation function H and some knowledge about the additive noise term n(x,y), the objective of restoration is to obtain an estimate f(x,y) of the original image.
H is a linear, position-invariant process, then the degraded image is given in the spatial domain by
f(x,y)= h(x,y)*f(x,y)+n(x,y) ……(1)
Where h(x,y) is the spatial representation of the degradation function and the symbol “*” indicates spatial convolution. Convolution in the spatial domain is equal to multiplication in the frequency domain, So we may write the model in equation (1) in an equivalent frequency domain representation.
G(u,v)= H(u,v)F(u,v)+N(u,v) ……(2)
Where the terms in capital letters are the Fourier transforms of the corresponding term in equation (1).