20 August 2001 Band selection from a hyperspectral data-cube for a real-time multispectral 3CCD camera
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul J. Withagen, Eric den Breejen, Eric M. Franken, Arie N. de Jong, Hans Winkel, "Band selection from a hyperspectral data-cube for a real-time multispectral 3CCD camera", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437054; https://doi.org/10.1117/12.437054

Back to Top