Share Email Print
cover

Proceedings Paper

Spectral/spatial hyperspectral image compression in conjunction with virtual dimensionality
Author(s): Bharath Ramakrishna; Jing Wang; Antonio Plaza; Hsuan Ren; Chein-Chi Chang; Janet L. Jensen; James O. Jensen
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Hyperspectral image compression can be performed by either 3-D compression or spectral/spatial compression. It has been demonstrated that due to high spectral resolution hyperspectral image compression can be more effective if compression is carried out spectrally and spatially in two separate stages. One commonly used spectral/spatial compression implements principal components analysis (PCA) or wavelet for spectral compression followed by a 2-D/3D compression technique for spatial compression. This paper presents another type of spectral/spatial compression technique, which uses Hyvarinen and Oja's Fast independent component analysis (FastICA) to perform spectral compression, while JPEG2000 is used for 2-D/3-D spatial compression. In order to determine how many independent components are required, a newly developed concept, virtual dimensionality (VD) is used. Since the VD is determined by the false alarm probability rather than the commonly used signal-to-noise ratio or mean squared error (MSE), our proposed FastICA-based spectral/spatial compression is more effective than PCA-based or wavelet-based spectral/spatial compression in data exploitation.

Paper Details

Date Published: 1 June 2005
PDF: 10 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.604128
Show Author Affiliations
Bharath Ramakrishna, Univ. of Maryland/Baltimore County (United States)
Jing Wang, Univ. of Maryland/Baltimore County (United States)
Antonio Plaza, Univ. of Maryland/Baltimore County (United States)
Univ. of Extremadura (Spain)
Hsuan Ren, National Central Univ. (Taiwan)
Chein-Chi Chang, Univ. of Maryland/Baltimore County (United States)
Janet L. Jensen, U.S. Army Edgewood Chemical and Biological Ctr. (United States)
James O. Jensen, U.S. Army Edgewood Chemical and Biological Ctr. (United States)


Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

© SPIE. Terms of Use
Back to Top