Quantization error and dynamic range considerations for compressive imaging systems design

Adrian Stern, Yigal Zeltzer, Yair Rivenson

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


A natural field of application for compressive sensing theory is imaging. Indeed, numerous compressive imaging (CI) systems and applications have been developed during the last few years. This work addresses the quantization effect in CI, which is fundamental for most CI architectures. In this paper, the implications of sensor quantization on universal CI are investigated theoretically and demonstrated with numerical experiments. It is shown that employing a CI framework may set severe requirements on the quantization depth of the optical sensor used. The quantization depth overhead requirement may be prohibitive in many optical imaging scenarios employing typical CI architectures. Practical solutions that significantly alleviate this requirement are suggested.

Original languageEnglish
Pages (from-to)1069-1077
Number of pages9
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Issue number6
StatePublished - 1 Jan 2013

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition


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