Spatial-spectral endmember extraction from hyperspectral imagery using multi-band morphology and volume optimization

Authors:
Antonio Plaza;Javier Plaza;Gabriel Martin
Affiliations:
Department of Technology of Computers and Communications, Escuela Politecnica de Caceres, University of Extremadura, Caceres, Spain;Department of Technology of Computers and Communications, Escuela Politecnica de Caceres, University of Extremadura, Caceres, Spain;Department of Technology of Computers and Communications, Escuela Politecnica de Caceres, University of Extremadura, Caceres, Spain
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 2
Cited 0

Morphological Image Analysis: Principles and Applications

Morphological Image Analysis: Principles and Applications
Hyperspectral Imaging: Techniques for Spectral Detection and Classification

Hyperspectral Imaging: Techniques for Spectral Detection and Classification

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Abstract

We develop a new approach for characterization of mixed pixels in remotely sensed hyperspectral images. The proposed method first performs joint spatial-spectral pixel characterization via extended morphological transformations, and then automatically extracts pure spectral signatures (called end-members) using volume optimization and convex geometry concepts. The proposed method outperforms other widely used approaches in the analysis of a real hyperspectral scene collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Ground-truth information available from U.S. Geological Survey is used to substantiate our findings.