The image restoration problem (also known as image deconvolution or image deblurring) is one of reconstruction or estimation of an undegraded image from a blurred and noisy one [Gon02,

Bov00]. In effect, the task is to undo the degradation imposed on the original image. The methods of image restoration described here all assume that the degradation is spatially invariant and that it can be modeled by linear filters and additive noise. Additionally, we assume that the degradation is known and that some characteristics of the noise are also known or can be estimated. Following a common convention, in the remainder of this section we refer to the blurring function or filter as the point spread function (

psf). Given an original image f[n

_{1},n

_{2}], a point spread function h[n

_{1},n

_{2}] and a noise signal w[n

_{1},n

_{2}] we obtain the following formulation for the observed, or degraded, image g[n

_{1},n

_{2}]: