Combined frequency and spatial domain algorithm for the removal of blocking artifacts
EURASIP Journal on Applied Signal Processing
Learning-Based Image Restoration for Compressed Image through Neighboring Embedding
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Short Communication: Efficient quadtree based block-shift filtering for deblocking and deringing
Journal of Visual Communication and Image Representation
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Learning-based image restoration for compressed images
Image Communication
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This paper presents a novel postprocessing algorithm developed specifically for very low bit-rate MC-DCT video coders operating at low spatial resolution, postprocessing is intricate in this situation because the low sampling rate (as compared to the image feature size) makes it very easy to overfilter, producing excessive blurring. The proposed algorithm uses pixel-by-pixel processing to identify and reduce both blocking artifacts and mosquito noise while attempting to preserve the sharpness and naturalness of the reconstructed video signal and minimize the system complexity. Experimental results show that the algorithm successfully reduces artifacts in a 16 kb/s scene-adaptive coder for video signals sampled at 80×112 pixels per frame and 5-10 frames/s. Furthermore, the portability of the proposed algorithm to other block-DCT based compression systems is shown by applying it, without modification, to successfully post-process a JPEG-compressed image