Abstract

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.

© 2013 Optical Society of America

Information optimal compressive sensing: static measurement design

Amit Ashok, Liang-Chih Huang, and Mark A. Neifeld
J. Opt. Soc. Am. A 30(5) 831-853 (2013)

Characterization of a compressive imaging system using laboratory and natural light scenes

Stephen J. Olivas, Yaron Rachlin, Lydia Gu, Brian Gardiner, Robin Dawson, Juha-Pekka Laine, and Joseph E. Ford
Appl. Opt. 52(19) 4515-4526 (2013)

Super-resolution compressive imaging with anamorphic optics

Vladimir Farber, Yitzhak August, and Adrian Stern
Opt. Express 21(22) 25851-25863 (2013)

Accurate image quantization adapted to multisource photometric reconstruction for rough textured surface analysis

Alexandre Bony, Benjamin Bringier, and Majdi Khoudeir
J. Opt. Soc. Am. A 30(3) 518-526 (2013)

Compressive hyperspectral imaging by random separable projections in both the spatial and the spectral domains

Yitzhak August, Chaim Vachman, Yair Rivenson, and Adrian Stern
Appl. Opt. 52(10) D46-D54 (2013)