Distortion-rate functions for quantized compressive sensing

We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore,...

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Bibliographic Details
Published in2009 IEEE Information Theory Workshop on Networking and Information Theory pp. 171 - 175
Main Authors Wei Dai, Hoa Vinh Pham, Milenkovic, O.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
Subjects
Application software
Computer simulation
Distortion measurement
Electric variables measurement
Extraterrestrial measurements
Image reconstruction
Quantization
Reconstruction algorithms
Signal reconstruction
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ISBN1424445353
9781424445356
DOI10.1109/ITWNIT.2009.5158565

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Summary:We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore, we adapt two well-known compressive sensing reconstruction algorithms to accommodate the quantization effects. The performance of the new reconstruction methods is assessed through extensive computer simulations.
ISBN:1424445353
9781424445356
DOI:10.1109/ITWNIT.2009.5158565