Unsupervised unmixing analysis based on multiscale representation

Maria C. Torres-Madronero; Miguel Velez-Reyes

doi:10.1117/12.920698

24 May 2012 Unsupervised unmixing analysis based on multiscale representation

Maria C. Torres-Madronero, Miguel Velez-Reyes

Author Affiliations +

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 83901O (2012) https://doi.org/10.1117/12.920698
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Automated unmixing consists of finding the number of endmembers, their spectral signatures and their abundances from a hyperspectral image. Most unmixing techniques are pixel-to-pixel procedures that do not take advantage of spatial information provided by hyperspectral sensor. This paper explores a new approach for unmixing analysis of hyperspectral imagery based on a multiscale representation for the joint estimation of the number of endmember and their spectral signatures. Experimental results using an AVIRIS image is presented.

Citation Download Citation

Maria C. Torres-Madronero and Miguel Velez-Reyes "Unsupervised unmixing analysis based on multiscale representation", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83901O (24 May 2012); https://doi.org/10.1117/12.920698

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