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
Models for patch-based image restoration
Journal on Image and Video Processing - Special issue on patches in vision
Short Communication: Efficient quadtree based block-shift filtering for deblocking and deringing
Journal of Visual Communication and Image Representation
Reconstructing videos from multiple compressed copies
IEEE Transactions on Circuits and Systems for Video Technology
Video enhancement from multiple compressed copies in transform domain
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
An image coding method by construction of variable block size and region compensation
MUSP'06 Proceedings of the 6th WSEAS international conference on Multimedia systems & signal processing
Learning-based image restoration for compressed images
Image Communication
A Total Variation-Based JPEG Decompression Model
SIAM Journal on Imaging Sciences
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A deblocking method based on projection onto convex sets (POCS) is proposed to reduce blocking artifacts in compressed images coded by the block discrete cosine transform. The method differs from existing POCS-based methods in three aspects. Firstly, the adjustment of a pixel's intensity is determined by local properties of the pixel. Secondly, three locally adaptive constraint sets are introduced to improve deblocking results. Thirdly, the human visual system modeling and relaxed projections are incorporated to make pixels adjust appropriately. The method is tested on typical images with excellent results.