A comparative study of compressed sensing video encoding GOP patterns for stereo distributed video coding

In this study, compressed sensing concepts are applied to multi-view video coding. Existing work from single view video is utilized to develop efficient GOP patterns and reference framing for stereo coding. It has been observed that the most typical choice of pattern improved the characteristics 0.4 dB with respect to the model that do not benefit from interview sparsity for all frames. Alternatives for future work are proposed.

[1]  Trac D. Tran,et al.  Distributed Compressed Video Sensing , 2009, 2009 43rd Annual Conference on Information Sciences and Systems.

[2]  E. Candès,et al.  Stable signal recovery from incomplete and inaccurate measurements , 2005, math/0503066.

[3]  Richard G. Baraniuk,et al.  Distributed Compressive Sensing , 2009, ArXiv.

[4]  E.J. Candes Compressive Sampling , 2022 .

[5]  Kannan Ramchandran,et al.  PRISM: A new robust video coding architecture based on distributed compression principles , 2002 .

[6]  Mourad Ouaret,et al.  Multiview Distributed Video Coding with encoder driven fusion , 2007, 2007 15th European Signal Processing Conference.

[7]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[8]  Luis Torres,et al.  A Comparison of Different Side Information Generation Methods for Multiview Distributed Video Coding , 2007, SIGMAP.

[9]  Stefano Tubaro,et al.  Distributed Video Coding: Trends and Perspectives , 2009, EURASIP J. Image Video Process..

[10]  R.G. Baraniuk,et al.  Distributed Compressed Sensing of Jointly Sparse Signals , 2005, Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005..

[11]  Mário A. T. Figueiredo,et al.  Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.

[12]  Thong T. Do,et al.  Sparsity adaptive matching pursuit algorithm for practical compressed sensing , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[13]  Deanna Needell,et al.  Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit , 2007, IEEE Journal of Selected Topics in Signal Processing.

[14]  E. Candès,et al.  Sparsity and incoherence in compressive sampling , 2006, math/0611957.

[15]  C. Guillemot,et al.  Distributed Monoview and Multiview Video Coding , 2007, IEEE Signal Processing Magazine.

[16]  Rui Zhang,et al.  Wyner-Ziv coding of motion video , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[17]  Thomas S. Huang,et al.  Distributed Video Coding using Compressive Sampling , 2009, 2009 Picture Coding Symposium.

[18]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[19]  Bernd Girod,et al.  Distributed Video Coding , 2005, Proceedings of the IEEE.

[20]  Gabriel Peyré,et al.  Best Basis Compressed Sensing , 2007, IEEE Transactions on Signal Processing.

[21]  Trac D. Tran,et al.  Fast compressive sampling with structurally random matrices , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[22]  Samuel Cheng,et al.  Distributed source coding: Theory and applications , 2010, 2010 18th European Signal Processing Conference.

[23]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[24]  Chun-Shien Lu,et al.  Distributed compressive video sensing , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.