1 June 2005 Endmember generation by projection pursuit
Author Affiliations +
Projection pursuit (PP) is an interesting concept, which has been found in many applications. It uses a so-called projection index (PI) as a criterion to seek directions that may lead to interesting findings for data analysts. Unlike the principal components analysis (PCA), which uses variance as a measure to find directions that maximizes data variances, the PI used by the PP finds interesting directions that can be characterized by statistics higher than variance. As a result, the PCA is generally considered as a special case of PP with the PI particularly specified by the variance. Recently, a PP-based approach was developed by Ifarraguerri and Chang for multispectral/hyperspectral image analysis. This paper revisits their approach and investigates its application in endmember generation where endmembers can be extracted from a sequence of projections generated by PP.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory Solyar, Gregory Solyar, Chein-I Chang, Chein-I Chang, Antonio Plaza, Antonio Plaza, } "Endmember generation by projection pursuit", Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.604137; https://doi.org/10.1117/12.604137

Back to Top