Signal Processing - Image and Video Coding beyond Standards
Convex Optimization
Reconstructing videos from multiple compressed copies
IEEE Transactions on Circuits and Systems for Video Technology
Dequantizing compressed sensing with non-Gaussian constraints
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
IEEE Transactions on Information Theory
Convex set theoretic image recovery by extrapolated iterations of parallel subgradient projections
IEEE Transactions on Image Processing
Set theoretic compression with an application to image coding
IEEE Transactions on Image Processing
Pointwise Shape-Adaptive DCT for High-Quality Denoising and Deblocking of Grayscale and Color Images
IEEE Transactions on Image Processing
Improved wavelet decoding via set theoretic estimation
IEEE Transactions on Circuits and Systems for Video Technology
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With the recent development of tools for data sharing in social networks and peer to peer networks, the same information is often stored in different nodes. Peer-to-peer protocols usually allow one user to collect portions of the same file from different nodes in the network, substantially improving the rate at which data are received by the end user. In some cases, however, the same multimedia document is available in different lossy versions on the network nodes. In such situations, one may be interested in collecting all available versions of the same document and jointly decoding them to obtain a better reconstruction of the original. In this paper we study some methods to jointly decode different versions of the same image. We compare different uses of the method of Projections Onto Convex Sets (POCS) with some Convex Optimization techniques in order to reconstruct an image for which JPEG and JPEG2000 lossy versions are available.