Paper
20 August 2001 Automated optimal channel selection for spectral imaging sensors
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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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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John H. Gruninger, Robert L. Sundberg, Marsha J. Fox, Robert Y. Levine, William F. Mundkowsky, Michael S. Salisbury, and Alan H. Ratcliff "Automated optimal channel selection for spectral imaging sensors", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); https://doi.org/10.1117/12.437052
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CITATIONS
Cited by 15 scholarly publications.
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KEYWORDS
Sensors

Signal processing

Imaging spectroscopy

Reflectivity

Image sensors

Data compression

Remote sensing

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