Multi-spectral compressive snapshot imaging using RGB image sensors

Hoover Rueda, Daniel Lau, Gonzalo R. Arce

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

Compressive sensing is a powerful sensing and reconstruction framework for recovering high dimensional signals with only a handful of observations and for spectral imaging, compressive sensing offers a novel method of multispectral imaging. Specifically, the coded aperture snapshot spectral imager (CASSI) system has been demonstrated to produce multi-spectral data cubes color images from a single snapshot taken by a monochrome image sensor. In this paper, we expand the theoretical framework of CASSI to include the spectral sensitivity of the image sensor pixels to account for color and then investigate the impact on image quality using either a traditional color image sensor that spatially multiplexes red, green, and blue light filters or a novel Foveon image sensor which stacks red, green, and blue pixels on top of one another.

Original languageEnglish
Pages (from-to)12207-12221
Number of pages15
JournalOptics Express
Volume23
Issue number9
DOIs
StatePublished - May 4 2015

Bibliographical note

Publisher Copyright:
© 2015 Optical Society of America.

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Multi-spectral compressive snapshot imaging using RGB image sensors'. Together they form a unique fingerprint.

Cite this