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Computational multispectral video imaging

Wang, Peng and Menon, Rajesh (2018) Computational multispectral video imaging. Journal of the Optical Society of America A, 35 (1). pp. 189-199. ISSN 1084-7529. http://resolver.caltech.edu/CaltechAUTHORS:20180111-134220861

[img] Video (QuickTime) (Visualization 1 - Original video on LCD screen) - Supplemental Material
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[img] Video (QuickTime) (Visualization 2 - Raw data from monochrome sensor) - Supplemental Material
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[img] Video (QuickTime) (Visualization 3 - Reconstructed RGB video from multispectral data) - Supplemental Material
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[img] Video (QuickTime) (Visualization 4 - Reconstructed multispectral video) - Supplemental Material
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Abstract

Multispectral imagers reveal information unperceivable to humans and conventional cameras. Here, we demonstrate a compact single-shot multispectral video-imaging camera by placing a micro-structured diffractive filter in close proximity to the image sensor. The diffractive filter converts spectral information to a spatial code on the sensor pixels. Following a calibration step, this code can be inverted via regularization-based linear algebra to compute the multispectral image. We experimentally demonstrated spectral resolution of 9.6 nm within the visible band (430–718 nm). We further show that the spatial resolution is enhanced by over 30% compared with the case without the diffractive filter. We also demonstrate Vis-IR imaging with the same sensor. Because no absorptive color filters are utilized, sensitivity is preserved as well. Finally, the diffractive filters can be easily manufactured using optical lithography and replication techniques.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1364/JOSAA.35.000189DOIArticle
https://www.osapublishing.org/josaa/abstract.cfm?uri=josaa-35-1-189PublisherArticle
Additional Information:© 2017 Optical Society of America. Received 2 June 2017; revised 19 November 2017; accepted 4 December 2017; posted 4 December 2017 (Doc. ID 297176); published 22 December 2017. Funding: U.S. Department of Energy (DOE) (EE0005959); National Aeronautics and Space Administration (NASA) (NNX14AB13G); Office of Naval Research (ONR) (N66001-10-1-4065). The authors would like to thank Dr. Eyal Shafran for assistance in compiling the multispectral video. We also acknowledge NKT Photonics for assistance with the super-continuum source and the tunable bandpass filter.
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)EE0005959
NASANNX14AB13G
Office of Naval Research (ONR)N66001-10-1-4065
Classification Code:OCIS codes: (110.1758) Computational imaging; (050.1970) Diffractive optics; (110.4234) Multispectral and hyperspectral imaging; (350.3950) Micro-optics; (100.3190) Inverse problems.
Record Number:CaltechAUTHORS:20180111-134220861
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180111-134220861
Official Citation:Peng Wang and Rajesh Menon, "Computational multispectral video imaging [Invited]," J. Opt. Soc. Am. A 35, 189-199 (2018)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84270
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:11 Jan 2018 23:41
Last Modified:11 Jan 2018 23:41

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