Distributed Compressed Video Sensing in Camera Sensor Networks
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Yu Liu | Sung Ho Cho | Zhang Lin | Xuqi Zhu
[1] Toshiaki Fujii,et al. The Adaptive Distributed Source Coding of Multi-View Images in Camera Sensor Networks , 2005, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..
[2] S. Mallat. A wavelet tour of signal processing , 1998 .
[3] Richard G. Baraniuk,et al. Bayesian Compressive Sensing Via Belief Propagation , 2008, IEEE Transactions on Signal Processing.
[4] 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.
[5] Xiaoming Huo,et al. Uncertainty principles and ideal atomic decomposition , 2001, IEEE Trans. Inf. Theory.
[6] R. A. McDonald,et al. Noiseless Coding of Correlated Information Sources , 1973 .
[7] Seishi Takamura. Distributed Video Coding: Trends and Future , 2006 .
[8] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[9] Lawrence Carin,et al. Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing , 2009, IEEE Transactions on Signal Processing.
[10] D. Donoho,et al. Counting faces of randomly-projected polytopes when the projection radically lowers dimension , 2006, math/0607364.
[11] Vahid Tarokh,et al. Shannon-Theoretic Limits on Noisy Compressive Sampling , 2007, IEEE Transactions on Information Theory.
[12] Martin Vetterli,et al. Rate Distortion Behavior of Sparse Sources , 2012, IEEE Transactions on Information Theory.
[13] Aaron D. Wyner,et al. Recent results in the Shannon theory , 1974, IEEE Trans. Inf. Theory.
[14] Trac D. Tran,et al. Distributed Compressed Video Sensing , 2009, 2009 43rd Annual Conference on Information Sciences and Systems.
[15] Anamitra Makur,et al. A compressive sensing approach to object-based surveillance video coding , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[16] Kannan Ramchandran,et al. PRISM: A new robust video coding architecture based on distributed compression principles , 2002 .
[17] Vahid Tarokh,et al. A Coding Theory Approach to Noisy Compressive Sensing Using Low Density Frames , 2011, IEEE Transactions on Signal Processing.
[18] Susanto Rahardja,et al. Wyner-Ziv Image Coding from Random Projections , 2007, 2007 IEEE International Conference on Multimedia and Expo.
[19] Chun-Shien Lu,et al. Distributed compressive video sensing , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.
[20] Aaron D. Wyner,et al. The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.
[21] Richard G. Baraniuk,et al. Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[22] Bernd Girod,et al. Distributed Video Coding , 2005, Proceedings of the IEEE.
[23] Feng Wu,et al. Analysis on Rate-Distortion Performance of Compressive Sensing for Binary Sparse Source , 2009, 2009 Data Compression Conference.
[24] Zixiang Xiong,et al. Layered Wyner-Ziv video coding , 2004, IS&T/SPIE Electronic Imaging.
[25] Richard G. Baraniuk,et al. An Architecture for Compressive Imaging , 2006, 2006 International Conference on Image Processing.
[26] Zhibo Chen,et al. A novel image/video coding method based on Compressed Sensing theory , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[27] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[28] E. Candès,et al. Sparsity and incoherence in compressive sampling , 2006, math/0611957.
[29] Richard G. Baraniuk,et al. Wavelet-domain hidden Markov models for signal detection and classification , 1997, Optics & Photonics.
[30] Emmanuel J. Candès,et al. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.