USING BLOCKS OF SKEWERS FOR FASTER COMPUTATION OF PIXEL PURITY INDEX
The pixel purity index (PPI) algorithm proposed by Boardman, et al.1 identifies potential endmember pixels in multispectral imagery. The algorithm generates a large number of skewers (unit vectors in random directions), and then computes the dot product of each skewer with each pixel. The PPI is incremented for those pixels associated with the extreme values of the dot products. A small number of pixels (a subset of those with the largest PPI values) are selected as pure and the rest of the pixels in the image are expressed as linear mixtures of these pure endmembers. This provides a convenient and physically-motivated decomposition of the image in terms of a relatively few components. We report on a variant of the PPI algorithm in which blocks of B skewers are considered at a time. From the computation of B dot products, one can produce a much larger set of derived dot products that are associated with skewers that are linear combinations of the original B skewers. Since the derived dot products involve only scalar operations, instead of full vector dot products, they can be very cheaply computed. We will also discuss a hardware implementation on a field programmable gate array (FPGA) processor both of the original PPI algorithm and of the block-skewer approach. We will furthermore discuss the use of fast PPI as a front-end to more sophisticated algorithms for selecting the actual endmembers.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- US Department of Energy (US)
- DOE Contract Number:
- W-7405-ENG-36
- OSTI ID:
- 766213
- Report Number(s):
- LA-UR-00-3002; TRN: US200207%%146
- Resource Relation:
- Conference: SPIE Conference Session AM 104, Imaging Spectrometry VI, San Diego, CA (US), 07/30/2000--08/04/2000; Other Information: Supercedes report DE00766213; PBD: 1 Oct 2000; PBD: 1 Oct 2000
- Country of Publication:
- United States
- Language:
- English
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