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12 May 2010 A novel method for change detection in spectral imagery
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Abstract
A new method for change detection of two large area scenes based on the point density of the pixel distribution in the hyperspace is presented. This method is derived from the point density approach to hyperspectral analysis, originally developed for material discrimination based on inherent dimension estimation. In this method, two registered large area scenes are tiled for individual scoring and comparison. The point density tail length is estimated for each tile in both scenes. The difference between this value for corresponding tiles indicates whether change has likely occurred in a tile and how significant the change is relative to other changes in the image. The method does not identify changes in individual pixels, but uses a tiling approach to identify changes in small sub-regions of the image. Preliminary results of this methodology are presented for multiple images and changing scene phenomenology.
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Ariel Schlamm, David Messinger, and William Basener "A novel method for change detection in spectral imagery", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 76951J (12 May 2010); https://doi.org/10.1117/12.849123
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