Blind restoration of space-invariant image degradations in the singular value decomposition domain

A new algorithm for blind restoration of space-invariant image degradations is presented. Once the singular value decomposition (SVD) of the degraded image is computed, degradation system identification and image restoration are performed through operations on singular vectors and singular values of the degraded image. The unknown point-spread function (PSF) is estimated from the singular vectors, while noise variance is estimated from the smallest singular values. It has been shown how to estimate the phase function for blurs that have zeros on the unit bicircle. Image restoration is performed through Wiener filtering of singular vectors. Knowledge about statistical properties of singular vectors and singular values is built into estimation and restoration procedures.