A hybrid parallel projection approach to object-based image restoration
Pattern Recognition Letters
Deringing cartoons by image analogies
ACM Transactions on Graphics (TOG)
Design a deblocking filter with three separate modes in DCT-based coding
Journal of Visual Communication and Image Representation
Design of a Deblocking Filter for Both Objective and Subjective Metrics
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Models for patch-based image restoration
Journal on Image and Video Processing - Special issue on patches in vision
Block effect reduction by the 1-D gray polynomial interpolation
Digital Signal Processing
ICCOM'06 Proceedings of the 10th WSEAS international conference on Communications
Learning-based image restoration for compressed images
Image Communication
A training-based method for reducing ringing artifact in BDCT-encoded images
EGMM'04 Proceedings of the Seventh Eurographics conference on Multimedia
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We present a new image recovery algorithm to remove, in addition to blocking, ringing artifacts from compressed images and video. This new algorithm is based on the theory of projections onto convex sets (POCS). A new family of directional smoothness constraint sets is defined based on line processes modeling of the image edge structure. The definition of these smoothness sets also takes into account the fact that the visibility of compression artifacts in an image is spatially varying. To overcome the numerical difficulty in computing the projections onto these sets, a divide-and-conquer (DAC) strategy is introduced. According to this strategy, new smoothness sets are derived such that their projections are easier to compute. The effectiveness of the proposed algorithm is demonstrated through numerical experiments using Motion Picture Expert Group based (MPEG-based) coders-decoders (codecs)