Maximum-likelihood parameter estimation for image ringing-artifact removal
IEEE transactions on circuits and systems for video technology (Print)
At low bit rates, image compression codecs based on overlapping transforms introduce spurious oscillations known as ringing artifacts in the vicinity of major edges. Unlike previous works, we present a maximum-likelihood approach to the ringingartifact removal problem. Our approach employs a parameter-estimation method based on the -means algorithm with the number of clusters determined by a cluster-separation measure. The proposed algorithm and its simplified approximation are applied to
... 00 compressed images. Our results show effective and efficient removal of ringing artifacts. . He also co-organizes several workshops on wavelets at MIT. His research interests are in the theory of wavelets and filter banks and applications in image and video compression, telecommunications, bioinformatics, medical imaging and enhancement, and analog/digital conversion. He is the coauthor (with G. Strang) of the popular textbook Wavelets and Filter Banks (Cambridge, MA: Wellesley-Cambridge Press, 1997) and the author of several Matlab-based toolboxes on image compression, electrocardiogram compression, and filter-bank design. He also holds a patent on an efficient design method for wavelets and filter banks and several patents on wavelet applications, including compression and signal analysis. Dr. WI, where he is the Chairman and CEO, responsible for guidging the development of new digital imaging technology. His research interests are in image sequence processing, objectbased image recovery, color processing, and the restoration of images degraded by compression and acquisition distortions. He holds patents and has published in the areas of content interactive multimedia, stereoscopic vedio compression, motion estmation, image formation, and recovery.