Hyperspectral integrated computational imaging

Lisa A. Cassis; Aaron Urbas; Robert A. Lodder

doi:10.1007/s00216-004-2979-1

Hyperspectral integrated computational imaging

Lisa A. Cassis, Aaron Urbas, Robert A. Lodder

Research output: Contribution to journal › Review article › peer-review

12 Scopus citations

Abstract

The various aspects related to hyperspectral integrated computational imaging (HICI) are discussed. A new trend in hyperspectral imaging is to speed the visual data processing and reduce data storage requirements by downloading some of the computation to the sensing detector. Lenslet arrays and masks can also be employed to encode spatial features of a hyperspectral image. Hyperspectral images capture both spectral information and information on sample container position and velocity.

Original language	English
Pages (from-to)	868-872
Number of pages	5
Journal	Analytical and Bioanalytical Chemistry
Volume	382
Issue number	4
DOIs	https://doi.org/10.1007/s00216-004-2979-1
State	Published - Jun 2005

Bibliographical note

Funding Information:
Acknowledgements This research was funded in part by KSEF-333-RDE-003, the NIH through HL58927, the NSF through DGE-9870691, and NIH and SESI through SC-NIAAA-93-01. The research is being carried out in part at the National Synchrotron Light Source, Brookhaven National Laboratory, which is supported by the US Department of Energy, Division of Materials Sciences and Division of Chemical Sciences, under Contract No. DE-AC02-98CH10886.

Funding

Acknowledgements This research was funded in part by KSEF-333-RDE-003, the NIH through HL58927, the NSF through DGE-9870691, and NIH and SESI through SC-NIAAA-93-01. The research is being carried out in part at the National Synchrotron Light Source, Brookhaven National Laboratory, which is supported by the US Department of Energy, Division of Materials Sciences and Division of Chemical Sciences, under Contract No. DE-AC02-98CH10886.

Funders	Funder number
Brookhaven National Laboratory (BNL)
Chemical Sciences, Geosciences, and Biosciences Division
Division of Materials Sciences and Engineering
NIH and SESI	SC-NIAAA-93-01
NSF	DGE-9870691
National Synchrotron Light Source
US Department of Energy
National Institutes of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)	R01HL058927

ASJC Scopus subject areas

Analytical Chemistry
Biochemistry

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10.1007/s00216-004-2979-1

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abstract = "The various aspects related to hyperspectral integrated computational imaging (HICI) are discussed. A new trend in hyperspectral imaging is to speed the visual data processing and reduce data storage requirements by downloading some of the computation to the sensing detector. Lenslet arrays and masks can also be employed to encode spatial features of a hyperspectral image. Hyperspectral images capture both spectral information and information on sample container position and velocity.",

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note = "Funding Information: Acknowledgements This research was funded in part by KSEF-333-RDE-003, the NIH through HL58927, the NSF through DGE-9870691, and NIH and SESI through SC-NIAAA-93-01. The research is being carried out in part at the National Synchrotron Light Source, Brookhaven National Laboratory, which is supported by the US Department of Energy, Division of Materials Sciences and Division of Chemical Sciences, under Contract No. DE-AC02-98CH10886.",

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AU - Urbas, Aaron

AU - Lodder, Robert A.

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AB - The various aspects related to hyperspectral integrated computational imaging (HICI) are discussed. A new trend in hyperspectral imaging is to speed the visual data processing and reduce data storage requirements by downloading some of the computation to the sensing detector. Lenslet arrays and masks can also be employed to encode spatial features of a hyperspectral image. Hyperspectral images capture both spectral information and information on sample container position and velocity.

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JO - Analytical and Bioanalytical Chemistry

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Hyperspectral integrated computational imaging

Abstract

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