Preface. 1. Removal of Blocking Artifacts Using a Hierarchical Bayesian Approach; R. Molina, et al. 2. A Stochastic Technique for the Removal of Artifacts in Compressed Images and Video; R. Llados-Bernaus, et al. 3. Image Recovery from Compressed Video Using Multichannel Regularization; Yongyi Yang, et al. 4. Subband Coded Image Reconstruction for Lossy Packet Networks; S.S. Hemami, R.M. Gray. 5. Video Coding Standards: Error Resilience and Concealment; M.R. Banham, J.C. Brailean. 6. Error-Resilient Standard-Compliant Video Coding; B. Girod, N. Färber. 7. Error Concealment in Encoded Video Streams; P. Salama, et al. 8. Error Concealment for MPEG-2 Video; S. Aign. 9. Combined Source-Channel Video Coding; K.N. Ngan, C.W. Yap. Index.
Signal Recovery Techniques for Image and Video Compression andTransmission establishes a bridge between the fields of signal recovery and image and video compression. Traditionally these fields have developed separately because the problems they examined were regarded as very different, and the techniques used appear unrelated. Recently, though, there is growing consent among the research community that the two fields are quite closely related. Indeed, in both fields the objective is to reconstruct the best possible signal from limited information. The field of signal recovery, which is relatively mature, has long been associated with a wealth of powerful mathematical techniques such as Bayesian estimation and the theory of projects onto convex sets (to name just two). This book illustrates for the first time in a complete volume how these techniques can be brought to bear on the very important problems of image and video compression and transmission. Signal Recovery Techniques for Image and Video Compression andTransmission, which is written by leading practitioners in both fields, is one of the first references that addresses this approach and serves as an excellent information source for both researchers and practicing engineers.
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