Quantization and Compressive Sensing

    •  Boufounos, P.T., Jacques, L., Krahmer, F., Saab, R., Quantization and Compressive Sensing, Compressed Sensing and Its Applications edition, March 2015.
      BibTeX TR2015-008 PDF
      • @book{Boufounos2015mar,
      • author = {Boufounos, P.T. and Jacques, L. and Krahmer, F. and Saab, R.},
      • title = {Quantization and Compressive Sensing},
      • year = 2015,
      • edition = {Compressed Sensing and Its Applications},
      • month = mar,
      • url = {}
      • }
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    Computational Sensing

Quantization is an essential step in digitizing signals, and, therefore, an indispensable component of any modern acquisition system. This chapter explores the interaction of quantization and compressive sensing and examines practical quantization strategies for compressive acquisition systems. Specifically, we first provide a brief overview of quantization and examine fundamental performance bounds applicable to any quantization approach. Next, we consider several forms of scalar quantizers, namely uniform, non-uniform, and 1-bit. We provide performance bounds and fundamental analysis, as well as practical quantizer designs and reconstruction algorithms that account for quantization. Furthermore, we provide an overview of Sigma-Delta () quantization in the compressed sensing context, and also discuss implementation issues, recovery algorithms and performance bounds. As we demonstrate, proper accounting for quantization and careful quantizer design has significant impact in the performance of a compressive acquisition system.