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Proceedings Paper

Automated optimal channel selection for spectral imaging sensors
Author(s): John H. Gruninger; Robert L. Sundberg; Marsha J. Fox; Robert Y. Levine; William F. Mundkowsky; Michael S. Salisbury; Alan H. Ratcliff
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Paper Abstract

A method of optimizing the selection of spectral channels in a spectral-spatial remote sensor has been developed that is applicable to the design of multispectral, hyperspectral and ultra spectral resolution sensors. The approach is based on an end member analysis technique that has been refined to select the most information dense channels. The algorithm operates sequentially and at any step in the sequence, the channel selected is the most independent form all previously selected channels. After the channel selection process, highly correlated channels, which are contiguous to those selected, can be merged to form bands. This process increases the signal to noise for the new broader spectral bands. The resulting bands, potentially of unequal width and spacing, collect the most uncorrelated spectral information present in the data. The band selection provides a physical interpretation of the data and has applications in spectral feature selection and data compression.

Paper Details

Date Published: 20 August 2001
PDF: 8 pages
Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437052
Show Author Affiliations
John H. Gruninger, Spectral Sciences, Inc. (United States)
Robert L. Sundberg, Spectral Sciences, Inc. (United States)
Marsha J. Fox, Spectral Sciences, Inc. (United States)
Robert Y. Levine, Spectral Sciences, Inc. (United States)
William F. Mundkowsky, Surface Optics Corp. (United States)
Michael S. Salisbury, Air Force Research Lab. (United States)
Alan H. Ratcliff, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 4381:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII
Sylvia S. Shen; Michael R. Descour, Editor(s)

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