Hierarchical CoSaMP for compressively sampled sparse signals with nested structure
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Mauro Biagi | Roberto Cusani | Stefania Colonnese | Gaetano Scarano | Stefano Rinauro | Katia Mangone | R. Cusani | G. Scarano | M. Biagi | S. Colonnese | S. Rinauro | Katia Mangone
[1] Alessandro Neri,et al. Reduced complexity modeling and reproduction of colored textures , 2000, IEEE Trans. Image Process..
[2] Emmanuel J. Candès,et al. Decoding by linear programming , 2005, IEEE Transactions on Information Theory.
[3] Patrizio Campisi,et al. Reduced complexity rotation invariant texture classification using a blind deconvolution approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] M. Rudelson,et al. On sparse reconstruction from Fourier and Gaussian measurements , 2008 .
[5] Lawrence Carin,et al. Bayesian Compressive Sensing , 2008, IEEE Transactions on Signal Processing.
[6] Yonina C. Eldar,et al. Robust Recovery of Signals From a Union of Subspaces , 2008, ArXiv.
[7] R. Vershynin. On the role of sparsity in Compressed Sensing and random matrix theory , 2009, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).
[8] J. Tropp,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, Commun. ACM.
[9] Lawrence Carin,et al. Exploiting Structure in Wavelet-Based Bayesian Compressive Sensing , 2009, IEEE Transactions on Signal Processing.
[10] Yonina C. Eldar,et al. Robust Recovery of Signals From a Structured Union of Subspaces , 2008, IEEE Transactions on Information Theory.
[11] Jared Tanner,et al. Improved Bounds on Restricted Isometry Constants for Gaussian Matrices , 2010, SIAM J. Matrix Anal. Appl..
[12] Volkan Cevher,et al. Model-Based Compressive Sensing , 2008, IEEE Transactions on Information Theory.
[13] Deanna Needell,et al. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, ArXiv.
[14] Chinmay Hegde,et al. Sampling and Recovery of Pulse Streams , 2010, IEEE Transactions on Signal Processing.
[15] Milica Stojanovic,et al. Random Access Compressed Sensing for Energy-Efficient Underwater Sensor Networks , 2011, IEEE Journal on Selected Areas in Communications.
[16] Michael B. Wakin,et al. The Restricted Isometry Property for block diagonal matrices , 2011, 2011 45th Annual Conference on Information Sciences and Systems.
[17] Antonio Ortega,et al. Depth map coding using graph based transform and transform domain sparsification , 2011, 2011 IEEE 13th International Workshop on Multimedia Signal Processing.
[18] Antonio Ortega,et al. Adaptive compressed sensing for depthmap compression using graph-based transform , 2012, 2012 19th IEEE International Conference on Image Processing.
[19] Michael B. Wakin,et al. The Restricted Isometry Property for Random Block Diagonal Matrices , 2012, ArXiv.
[20] Deanna Needell,et al. Stable Image Reconstruction Using Total Variation Minimization , 2012, SIAM J. Imaging Sci..
[21] Bob L. Sturm,et al. Behavior of greedy sparse representation algorithms on nested supports , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[22] Roberto Cusani,et al. Efficient compressive sampling of spatially sparse fields in wireless sensor networks , 2013, EURASIP J. Adv. Signal Process..
[23] Roberto Cusani,et al. Bayesian prior for reconstruction of compressively sampled astronomical images , 2013, European Workshop on Visual Information Processing (EUVIP).
[24] Dimitris A. Pados,et al. Decoding of framewise compressed-sensed video via interframe total variation minimization , 2013, J. Electronic Imaging.
[25] Mauro Biagi,et al. Reconstruction of compressively sampled texture images in the graph-based transform domain , 2014, 2014 IEEE International Conference on Image Processing (ICIP).