Artifact reduction in low bit rate DCT-based image compression
IEEE Transactions on Image Processing
Removing the blocking artifacts of block-based DCT compressed images
IEEE Transactions on Image Processing
Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts
IEEE Transactions on Circuits and Systems for Video Technology
Efficient DCT-domain blind measurement and reduction of blocking artifacts
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Blocking artifacts suppression in block-coded images using overcomplete wavelet representation
IEEE Transactions on Circuits and Systems for Video Technology
DCT quantization noise in compressed images
IEEE Transactions on Circuits and Systems for Video Technology
Spatiotemporal sequence matching for efficient video copy detection
IEEE Transactions on Circuits and Systems for Video Technology
A deblocking method for BDCT compressed images based on adaptive projections
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Block artifact reduction using a transform-domain Markov random field model
IEEE Transactions on Circuits and Systems for Video Technology
Consistent image decoding from multiple lossy versions
Proceedings of the 2010 ACM workshop on Advanced video streaming techniques for peer-to-peer networks and social networking
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
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A single source video may be compressed using ditTerent encoders with different settings. In the context of online video sharing, many such video copies exist, and an end user may have access to a few of them and would like to reconstruct a video sequence with quality superior to all available copies. In this paper, we propose a scheme to improve the video quality by projecting the reconstructed video onto the quantization constraint sets defined by multiple video copies. Experimental results show that the proposed method is capable of improving video quality both subjectively and objectively.