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Compressive Sensing Reconstruction Based on the Quantization Constraint Sets  

Kim, Dong-Sik (Department of Electronics and Information Engineering, Hankuk University of Foreign Studies)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.46, no.5, 2009 , pp. 8-14 More about this Journal
Abstract
In this paper, a convex optimization technique, which is based on the generalized quantization constraint (GQC), is proposed in the compressive sensing reconstruction using quantized measures. The set size of the proposed GQC can be controlled, and through extensive numerical simulations based on the uniform scalar quantizers, the CS reconstruction errors are improved by 3.4-3.6dB compared to the traditional QC method for the CS problems of m/klogn > 2.
Keywords
compressive sensing; convex optimization; generalized quantization constraint; quantization;
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