RGB detectors on compressive snapshot multi-spectral imagers

Hoover Rueda; Daniel Lau; Gonzalo R. Arce

doi:10.1109/GlobalSIP.2015.7418223

RGB detectors on compressive snapshot multi-spectral imagers

Hoover Rueda, Daniel Lau, Gonzalo R. Arce

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

The coded aperture snapshot spectral imager (CASSI) system has been demonstrated to produce spectral images using just a single snapshot taken by a monochrome image sensor. In this paper, we introduce the use of color image sensors in CASSI to include the spectral sensitivity of the image sensor pixels to account for color and then investigate the impact on image quality. We analyze the use of the traditional Bayer color filter array image sensor, and the novel Foveon image sensor which stacks red, green, and blue pixels on top of one another. Several simulations on different 3D spatio-spectral databases show improvements of up to 3 dBs in terms of PSNR over traditional monochrome sensors.

Original language	English
Title of host publication	2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
Pages	388-392
Number of pages	5
ISBN (Electronic)	9781479975914
DOIs	https://doi.org/10.1109/GlobalSIP.2015.7418223
State	Published - Feb 23 2016
Event	IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States Duration: Dec 13 2015 → Dec 16 2015

Publication series

Name	2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Conference

Conference	IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
Country/Territory	United States
City	Orlando
Period	12/13/15 → 12/16/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Funding

Funders	Funder number
National Science Foundation Arctic Social Science Program	1538950, 1539157
National Science Foundation Arctic Social Science Program

Keywords

Compressive sensing
RGB detectors
coded apertures
hyperspectral imaging
optical imaging

ASJC Scopus subject areas

Information Systems
Signal Processing

Access to Document

10.1109/GlobalSIP.2015.7418223

Cite this

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title = "RGB detectors on compressive snapshot multi-spectral imagers",

abstract = "The coded aperture snapshot spectral imager (CASSI) system has been demonstrated to produce spectral images using just a single snapshot taken by a monochrome image sensor. In this paper, we introduce the use of color image sensors in CASSI to include the spectral sensitivity of the image sensor pixels to account for color and then investigate the impact on image quality. We analyze the use of the traditional Bayer color filter array image sensor, and the novel Foveon image sensor which stacks red, green, and blue pixels on top of one another. Several simulations on different 3D spatio-spectral databases show improvements of up to 3 dBs in terms of PSNR over traditional monochrome sensors.",

keywords = "Compressive sensing, RGB detectors, coded apertures, hyperspectral imaging, optical imaging",

author = "Hoover Rueda and Daniel Lau and Arce, \{Gonzalo R.\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 ; Conference date: 13-12-2015 Through 16-12-2015",

year = "2016",

month = feb,

day = "23",

doi = "10.1109/GlobalSIP.2015.7418223",

language = "English",

series = "2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015",

pages = "388--392",

booktitle = "2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015",

}

Rueda, H, Lau, D & Arce, GR 2016, RGB detectors on compressive snapshot multi-spectral imagers. in 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015., 7418223, 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015, pp. 388-392, IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015, Orlando, United States, 12/13/15. https://doi.org/10.1109/GlobalSIP.2015.7418223

RGB detectors on compressive snapshot multi-spectral imagers. / Rueda, Hoover; Lau, Daniel; Arce, Gonzalo R.
2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015. 2016. p. 388-392 7418223 (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lau, Daniel

AU - Arce, Gonzalo R.

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N2 - The coded aperture snapshot spectral imager (CASSI) system has been demonstrated to produce spectral images using just a single snapshot taken by a monochrome image sensor. In this paper, we introduce the use of color image sensors in CASSI to include the spectral sensitivity of the image sensor pixels to account for color and then investigate the impact on image quality. We analyze the use of the traditional Bayer color filter array image sensor, and the novel Foveon image sensor which stacks red, green, and blue pixels on top of one another. Several simulations on different 3D spatio-spectral databases show improvements of up to 3 dBs in terms of PSNR over traditional monochrome sensors.

AB - The coded aperture snapshot spectral imager (CASSI) system has been demonstrated to produce spectral images using just a single snapshot taken by a monochrome image sensor. In this paper, we introduce the use of color image sensors in CASSI to include the spectral sensitivity of the image sensor pixels to account for color and then investigate the impact on image quality. We analyze the use of the traditional Bayer color filter array image sensor, and the novel Foveon image sensor which stacks red, green, and blue pixels on top of one another. Several simulations on different 3D spatio-spectral databases show improvements of up to 3 dBs in terms of PSNR over traditional monochrome sensors.

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RGB detectors on compressive snapshot multi-spectral imagers

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

Access to Document

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