Automated Gaussian spectral clustering of hyperspectral data

Scott G. Beaven; Geoffrey G. Hazel; Alan D. Stocker

doi:10.1117/12.478758

2 August 2002 Automated Gaussian spectral clustering of hyperspectral data

Scott G. Beaven, Geoffrey G. Hazel, Alan D. Stocker

Proceedings Volume 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII; (2002) https://doi.org/10.1117/12.478758
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Unsupervised classification of multispectral and hyperspectral data is useful for a range of military and commercial remote sensing applications. These include terrain categorization, material detection and identification, and land use quantification. Here we show the development and application of an adaptive Gaussian Spectral Clustering approach to unsupervised classification of hyperspectral data. The method is built on adaptively estimating the parameters of a Gaussian mixture model from over local regions, and includes methods for adjusting to inevitable non-stationarity of hyperspectral image data. The algorithm is suitable for application to streaming hyperspectral data as would be required for real-time applications. In this paper we outline the model used, estimation techniques, and methods for adaptively estimating key model parameters required to characterize hyperspectral imagery. The key elements of the approach are demonstrated on reflective band hyperspectral data from NRL WarHORSE and NASA AVIRIS hyperspectral imagery.

Citation Download Citation

Scott G. Beaven, Geoffrey G. Hazel, and Alan D. Stocker "Automated Gaussian spectral clustering of hyperspectral data", Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); https://doi.org/10.1117/12.478758

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available