Share Email Print
cover

Proceedings Paper

Bandwidth compression of hyperspectral imagery data using a simplified KLT/JPEG 2000 approach
Author(s): John A. Saghri; Andrew G. Tescher; Anthony M. Planinac
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

A viable lossy bandwidth compression for hyperspectral imagery is presented. The algorithm is leveraged on the standard JPEG 2000 technology. The component decorrelation of the JPEG 2000 (extension 2) is replaced with a two-level Karhunen-Loeve Transformation (KLT) operation resulting in a reduction in the computation complexity. The set of n2 hyperspectral imagery is arranged as an n by n mosaic. Each of the n columns of the mosaic is spectrally uncorrelated via a first-level KLT operation. The resulting n principal component (PC) images for each column are placed next to one another to form an n by n mosaic of PC images. A second-level KLT is then applied to the first four rows of the n by n PC mosaic to approximate a full spectral decorrelation. This approach reduces the computational complexity of the KLT spectral decorrelation process of JPEG 2000 since, 1) it uses a smaller and computationally more feasible KLT matrix (i.e., n by n KLT matrix instead of size n2 by n2) and 2) it reduces the number of required computations for spectral decorrelation by a factor of n/4.

Paper Details

Date Published: 2 November 2004
PDF: 7 pages
Proc. SPIE 5558, Applications of Digital Image Processing XXVII, (2 November 2004); doi: 10.1117/12.564465
Show Author Affiliations
John A. Saghri, California Polytechnic State Univ. (United States)
Andrew G. Tescher, AGT Associates (United States)
Anthony M. Planinac, California Polytechnic State Univ. (United States)


Published in SPIE Proceedings Vol. 5558:
Applications of Digital Image Processing XXVII
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top