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Proceedings Paper

Near-lossless bandwith compression for radiometric data
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Paper Abstract

A bandwidth-compression scheme is presented based on spectral and spatial data correlations that can be used to transmit radiometric data collected by sensitive high-resolution sensors. The Karhunen-Loeve transformation is employed to remove spectral correlation, after which the data are treated with an adaptive discrete-cosine-transform coding technique. Coding errors are spread over entire individual data blocks after reconstruction because the coding is done in the transform domain. The technique reduces bandwidth while maintaining near-lossless coding, the ability to handle a high dynamic range, and the establishment of a maximum-coding-error upper bound. The approach is capable of some feature-classification capability, and each image is a blend of data from the entire set of spectral images. The method for bandwidth compression therefore permits the evaluation of a range of information without examining all images in the data set

Paper Details

Date Published: 1 November 1990
PDF: 11 pages
Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); doi: 10.1117/12.23511
Show Author Affiliations
John A. Saghri, Lockheed Palo Alto Research Lab. (United States)
Andrew G. Tescher, Lockheed Palo Alto Research Lab. (United States)

Published in SPIE Proceedings Vol. 1349:
Applications of Digital Image Processing XIII
Andrew G. Tescher, Editor(s)

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