Share Email Print

Journal of Applied Remote Sensing

Impact of JPEG2000 compression on endmember extraction and unmixing of remotely sensed hyperspectral data
Author(s): Gabriel Martin; Vicente González Ruiz; Antonio J. Plaza; Juan P. Ortiz; Inmaculada García Fernández
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Lossy hyperspectral image compression has received considerable interest in recent years due to the extremely high dimensionality of the data. However, the impact of lossy compression on spectral unmixing techniques has not been widely studied. These techniques characterize mixed pixels (resulting from insufficient spatial resolution) in terms of a suitable combination of spectrally pure substances (called endmembers) weighted by their estimated fractional abundances. This paper focuses on the impact of JPEG2000-based lossy compression of hyperspectral images on the quality of the endmembers extracted by different algorithms. The three considered algorithms are the orthogonal subspace projection (OSP), which uses only spatial information, and the automatic morphological endmember extraction (AMEE) and spatial spectral endmember extraction (SSEE), which integrate both spatial and spectral information in the search for endmembers. The impact of compression on the resulting abundance estimation based on the endmembers derived by different methods is also substantiated. Experimental results are conducted using a hyperspectral data set collected by NASA Jet Propulsion Laboratory over the Cuprite mining district in Nevada. The experimental results are quantitatively analyzed using reference information available from U.S. Geological Survey, resulting in recommendations to specialists interested in applying endmember extraction and unmixing algorithms to compressed hyperspectral data.

Paper Details

Date Published: 1 July 2010
PDF: 25 pages
J. Appl. Rem. Sens. 4(1) 041796 doi: 10.1117/1.3474975
Published in: Journal of Applied Remote Sensing Volume 4, Issue 1
Show Author Affiliations
Gabriel Martin, Univ. de Extremadura (Spain)
Vicente González Ruiz, Univ. de Almería (Spain)
Antonio J. Plaza, Univ. de Extremadura (Spain)
Juan P. Ortiz, Univ. de Almería (Spain)
Inmaculada García Fernández, Univ. de Almería (Spain)

© SPIE. Terms of Use
Back to Top