Adaptive fuzzy filtering for artifact reduction in compressed images and videos
IEEE Transactions on Image Processing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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As TV screens get ever larger, viewer tolerance to noise and artifacts has steadily declined. For next generation TVs, such as flat TV, LCoS (liquid crystal on silicon), etc., excellent picture quality becomes a distinguishing feature. Although the quality of most digital signals has significantly been improved, distortion and noise still creep in and are an important source of picture degradations. Post-processing is a sensible solution that achieves a visual enhancement of the reconstructed images. Some of the artifacts, such as blocking and ringing, have already been widely considered. Therefore, this paper concentrates on a novel post-processing technique that reduces another kind of distortion known as "mosquito noise". This temporal "busyness" is discarded by applying an adaptive temporal filter that preserves sharpness and naturalness of the reconstructed video signal in the frequency domain. The proposed mosquito noise reducer (MNR) algorithm is effective and straightforward to implement; experimental results show that the temporal post-filtering process significantly improves the visual quality of video sequences. Moreover, the architectural options allow flexibility and cost trade-off.