http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-74735 Adaptive Filtering using Channel

Abstract This review article gives an overview on adaptive filtering methods based on channel representations. The framework of channel representations and its re-lation to density estimation is introduced. The fast and accurate scheme of virtual shift decoding is introduced and applied in several variants of channel smoothing: • channel smoothing with alpha-synthesis for improving stability of edge-enhancing filtering • orientation adaptive channel smoothing with applications to coherence-enhancing filtering • channel smoothing using graph-cuts for improving filtering results at corners • channel-coded feature maps (CCFMs) which lead to a significant speed-up of channel averaging • CCFM-based smoothing based on optimal parameters derived from a novel un-certainty relation For each method, an algorithmic description and some examples of results are pro-vided, together with discussions and references of the original papers. Cross con-nections to other articles in this volume are given where appropriate.