Reduction of coding artifacts at low bit rates

Many video and image coding standards such as MPEG, H.261, H.263, and JPEG are based on the discrete cosine transform (DCT). They subdivide images or frames into blocks that are encoded independently. DCT coefficients that are considered to be less important are discarded. The achievable compression ratios are normally limited by visible discontinuities along block boundaries, the so called blocking artifacts. In this paper, a postprocessing algorithm based on Markov random fields (MRF) is proposed that efficiently removes blocking effects, while retaining the sharpness of the image and without introducing new artifacts. To prevent blurring of dominant edges, the decoded image is segmented into regions which are then enhanced separately. The segmentation is performed in two steps. A novel texture detector first identifies all texture regions, before the remaining monotone areas are partitioned by an MRF segmentation algorithm. A new edge component has been incorporated to improve the detection of dominant edges. The proposed enhancement stage calculates the MAP estimate of the unknown original image, which is modeled by an MRF. An efficient implementation is presented, end experiments demonstrate that our proposed postprocessor gives very good results both objectively and subjectively.