Adaptive fuzzy filtering for artifact elimination in compressed images and videos

Block-based Discrete Cosine Transform (DCT) image and video compression methods have been successfully used in image and video compression applications due to bandwidth and storage limitations. However, compression distortion becomes significant when these algorithms are used under a certain bit rate. The most noticeable degradations of block transform coding are blocking and ringing artifacts.In this thesis, two new adaptive post-filtering algorithms are proposed to remove observed coding artifacts as a result of DCT based image and video compression standards at low bit rates. With identification of coding artifact strength, fuzzy filter is applied by adjusting filtering range and its parameters.Experimental results showed that, the proposed algorithms exhibit better detail preservation and artifact removal performance with lower computational cost as compared to other post-processing techniques. Accordingly, these can be used for the real time image and video applications without undesired artifacts.