Degradation And Restoration In Digital Image Processing
Degradation And Restoration In Digital Image Processing
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).