At low bit rates, image compression codecs based on overlapping transforms introduce spurious oscillation known as ringing artifacts in the vicinity of major edges. The image quality can be enhanced considerably by removing the artifacts. We present a maximum likelihood approach to the ringing artifact removal problem. Our approach employs a parameter estimation method based on the k-means algorithm with the number of clusters determined by a cluster separation measure. The proposed algorithm and its simplified approximation are applied to JPEG2000 compressed images to demonstrate their effectiveness.
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