A new regularized approach and its applications in image restoration

The joint optimization of different criteria is addressed as a powerful means of incorporating prior information in linear image restoration algorithms. The resolution-to-noise-tradeoff (RNT) approach introduced enables the incorporation of both spatial and spectral information regarding the peculiarities of the problem. Depending on the nature of the spatial information, this approach can be interpreted as either a regularized or an adaptive scheme. As a regularized scheme, it offers an alternative to conventional approaches, in which the ringing artifacts, especially those due to the noise, are efficiently suppressed by means of the regularizing functional. As an adaptive scheme, the RNT approach offers the flexibility of applying either linear Wiener filtering, or inverse filtering, or no filtering at all, depending on the local signal-activity. The capabilities of the RNT approach as both a regularized and an adaptive scheme are demonstrated through restoration examples