
Proceedings Paper
An adaptive two-stage KLT scheme for spectral decorrelation in hyperspectral bandwidth compressionFormat | Member Price | Non-Member Price |
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Paper Abstract
A computationally efficient adaptive 2-stage Karhunen-Loeve Transform (KLT) scheme for spectral decorrelation in
hyperspectal lossy bandwidth compression is presented. The component decorrelation of the JPEG 2000 (extension
2) is replaced with the proposed adaptive 2-stage KLT spectral decorrelation scheme. Direct application of a single
KLT across the entire set of hyperspectal imagery may not be computationally practical. The proposed scheme
alleviates this problem by partitioning the spectral data set into small subsets. The spectral correlation within each
partition is removed via the 1st-stage KLT operation. To remove the remaining inter-partition correlation, a 2nd-stage
KLT is applied to the top few sets of eaui-level principal component (PC) images from the 1st-stage. The
computation savings resulting from 2-stage KLT is parametrically quantified. The proposed adaptive 2-stage KLT
uses only a fraction of the equi-level 1st-stage PC images in the 2nd-stage KLT process. This adaptive scheme results
in reducing the size of the 2nd-stage KLT transformation matrices and further improvement in computational
complexity and coding efficiency. It is shown that reconstructed image quality, as measured via statistical and/or
machine-based exploitation measures, is improved by using a smaller partition size in the 1st-stage KLT. A criterion
based on the components of the eigenvectors of the cross-covariance matrix is established to identify such 1st-stage
PC images. The proposed adaptive spectral decorrelation scheme also reduces the overhead bits required to transmit
the covariance matrices, or eigenvectors, along the coding bit stream to the receiver through the downlink channel.
Paper Details
Date Published: 2 September 2009
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 744313 (2 September 2009); doi: 10.1117/12.829000
Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)
PDF: 12 pages
Proc. SPIE 7443, Applications of Digital Image Processing XXXII, 744313 (2 September 2009); doi: 10.1117/12.829000
Show Author Affiliations
John A. Saghri, California Polytechnic State Univ., San Louis Obispo (United States)
Seton Schroeder, California Polytechnic State Univ., San Louis Obispo (United States)
Seton Schroeder, California Polytechnic State Univ., San Louis Obispo (United States)
Andrew G. Tescher, AGT Associates (United States)
Published in SPIE Proceedings Vol. 7443:
Applications of Digital Image Processing XXXII
Andrew G. Tescher, Editor(s)
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