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Band selection from a hyperspectral data-cube for a real-time multispectral 3CCD camera


Author: Withagen, P.J. · Breejen, E. den · Franken, E.M. · Jong, A.N. de · Winkel, J.
Place: Bellingham,WA
Institution: TNO Fysisch en Elektronisch Laboratorium
Source:Shen, S.S.Descour, M.R., Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, 16-19 April 2001, Orlando, FL, USA, 84-93
Proceedings of SPIE - The International Society for Optical Engineering
Identifier: 95382
doi: doi:10.1117/12.437054
Keywords: Physics


Given a specific task, like detection of hidden objects (i.e. vehicles and landmines) in a natural background, hyperspectral data gives a significant advantage over RGB-color or gray-value images. It introduces however, a trade-off between cost, speed, signal-to-noise ratio, spectral resolution, and spatial resolution. Our research concentrates on making an optimal choice for spectral bands in an imaging system with a high frame rate and spatial resolution. This can be done using a real-time multispectral 3CCD camera, which records a scene with three detectors, each accurately set to a wavelength by selected optical filters. This leads to the subject of this paper:, how to select three optimal bands from hyperspectral data to perform a certain task. The choice of these bands includes two aspects, the center wavelength, and the spectral width. A band-selection and band-broadening procedure has been developed, based on statistical pattern recognition techniques. We will demonstrate our proposed band selection algorithm, and present its classification results compared to red-green-blue and red-green-near-infrared data for a military vehicle in a natural background and for surface laid landmines in vegetation.