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Issue No.11 - November (2007 vol.29)
pp: 1891-1903
ABSTRACT
Subpixel detection is a challenging problem in hyperspectral imagery analysis. Since the target size is smaller than the size of a pixel, detection algorithms must rely solely on spectral information. A number of different algorithms have been developed over the years to accomplish this task, but most detectors have taken either a purely statistical or a physics-based approach to the problem. We present two new hybrid detectors that take advantage of these approaches by modeling the background using both physics and statistics. Results demonstrate improved performance over the well known AMSD and ACE subpixel algorithms in experiments that include multiple targets, images, and area types -- especially when dealing with weak targets in complex backgrounds.
INDEX TERMS
Target detection, subspace detectors, hyperspectral data, spectral mixture models
CITATION
Joshua Broadwater, Rama Chellappa, "Hybrid Detectors for Subpixel Targets", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.29, no. 11, pp. 1891-1903, November 2007, doi:10.1109/TPAMI.2007.1104
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