A comparative study of quantized compressive sensing schemes

Authors:
Wei Dai;Hoa Vinh Pham;Olgica Milenkovic
Affiliations:
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign;Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign;Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
Venue:
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Year:
2009

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Abstract

We study the average distortion introduced by scalar, vector, and entropy coded quantization of compressive sensing (CS) measurements. The asymptotic behavior of the underlying quantization schemes is either quantified exactly or characterized via bounds. We also modify two benchmark CS reconstruction algorithms to accommodate quantization effects, and empirically demonstrate that these methods significantly reduce the reconstruction distortion.