Iterative algorithm for image filtering utilizing image- and noise-related information

Abstract

Filtering of noise-corrupted images is an important problem in image processing. We propose several iterative algorithms for image filtering that are based on the minimization of the penalty functional describing the properties of both image and noise data. Applications of the proposed approach to image estimation from the ensemble of the noisy estimates, incomplete noisy input data, and the impulse noise ensemble are described. The demonstrated simulation results indicate that the proposed approach is applicable to some important image-filtering probems.