Using source separation methods for endmember selection

Chia-Yun Kuan; Glenn Healey

doi:10.1117/12.478745

2 August 2002 Using source separation methods for endmember selection

Chia-Yun Kuan, Glenn Healey

Proceedings Volume 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII; (2002) https://doi.org/10.1117/12.478745
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

We develop a method for automatic end-member selection in hyperspectral images. The method models a hyperspectral pixel as a linear mixture of an unknown number of materials. In contrast to many end-member selection methods, the new method selects end-members based on the statistics of large numbers of pixels rather than attempting to identify a small number of the purest pixels. The method is based on maximizing the independence of material abundances at each pixel. We show how independent component analysis algorithms can be adapted for use with this problem. We show properties of the method by application to synthetic hyperspectral data.

Citation Download Citation

Chia-Yun Kuan and Glenn Healey "Using source separation methods for endmember selection", Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); https://doi.org/10.1117/12.478745

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