Share Email Print
cover

Proceedings Paper

Lossless hyperspectral image compression via linear prediction
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper proposes an interband version of the linear prediction approach for hyperspectral images. Linear prediction represents one of the best performing and most practical and general purpose lossless image compression techniques known today. The interband linear prediction method consists of two stages: predictive decorrelation producing residuals and entropy coding of the residuals. Our method achieved a compression ratio in the range of 3.02 to 3.14 using 13 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images.

Paper Details

Date Published: 2 August 2002
PDF: 9 pages
Proc. SPIE 4725, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, (2 August 2002); doi: 10.1117/12.478794
Show Author Affiliations
Jarno S. Mielikainen, Lappeenranta Univ. of Technology (Finland)
Arto Kaarna, Lappeenranta Univ. of Technology (Finland)
Pekka J. Toivanen, Lappeenranta Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 4725:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

© SPIE. Terms of Use
Back to Top