Unsupervised hyperspectral image analysis using an advanced mixture model

Bradley S. Denney; Katia Estabridis; Rui J. P. de Figueiredo

doi:10.1117/12.487492

23 September 2003 Unsupervised hyperspectral image analysis using an advanced mixture model

Bradley S. Denney, Katia Estabridis, Rui J. P. de Figueiredo

Proceedings Volume 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX; (2003) https://doi.org/10.1117/12.487492
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Hyperspectral image analysis is an important component of advanced hyperspectral image understanding. We present a new approach that identifies unique materials and the abundance of these materials in a hyperspectral image. This approach uses physical constraints on material abundances and reflectances, and avoids the presence of a dark material class by parameterizing pixel illumination. The results are optimally generated in both supervised and unsupervised modes. Applications of the image analysis approach are also presented.

Citation Download Citation

Bradley S. Denney, Katia Estabridis, and Rui J. P. de Figueiredo "Unsupervised hyperspectral image analysis using an advanced mixture model", Proc. SPIE 5093, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery IX, (23 September 2003); https://doi.org/10.1117/12.487492

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KEYWORDS

Hyperspectral imaging

Image analysis

Roads

RGB color model

Fuzzy logic

Chemical elements

Sun

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