Fast unsupervised extraction of endmembers spectra from hyperspectral data

Jose M. P. Nascimento; Jose M. Bioucas Dias

doi:10.1117/12.510663

13 February 2004 Fast unsupervised extraction of endmembers spectra from hyperspectral data

Jose M. P. Nascimento, Jose M. Bioucas Dias

Proceedings Volume 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III; (2004) https://doi.org/10.1117/12.510663
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

Linear unmixing decomposes an hyperspectral image into a collection of reflectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.

Citation Download Citation

Jose M. P. Nascimento and Jose M. Bioucas Dias "Fast unsupervised extraction of endmembers spectra from hyperspectral data", Proc. SPIE 5239, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology III, (13 February 2004); https://doi.org/10.1117/12.510663

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