Image de-noising and restoration using wavelet transform

Image de-noising and restoration represent basic problems in image processing with many different applications including engineering, reconstruction of missing data during their transmission and enhancement of biomedicai structures as well. This problem occurs also in filling-in blocks of missing or corrupted data. The paper presents the use of Wavelet transform in this area including its application for image decomposition and rejection of its components at first. The main part of the paper is devoted (i) to algorithms of restoration of missing image blocks by the search of similar structures of a given image in the Wavelet domain space and (ii) to comparison of this approach with iterated Wavelet interpolation and predictive image modelling. Proposed methods are verified for simulated data and then applied for processing of magnetic resonance images.