Noise updating repeated Wiener filter and other adaptive noise smoothing filters using local image statistics

Abstract

We consider the restoration of images degraded by a class of signal-uncorrelated noise, which is possibly signal-dependent. Some adaptive noise smoothing filters, which assume a nonstationary mean, nonstationary variance image model implicitly or explicitly, are reviewed, and their performances are compared by the mean-squares errors (MSES) and by the human subjective judgment. We also present a new noise smoothing technique which is called the noise updating repeated Wiener (NURW) filter. Explicit noise variance updating formulas are derived for the NURW filter. The performance is improved both in the MSE sense and in the vicinity of edges by subjective observation.