Share Email Print
cover

Proceedings Paper

Lossless compression of 3D hyperspectral sounder data using the wavelet and Burrows-Wheeler transforms
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Hyperspectral sounder data is used for retrieval of useful geophysical parameters which promise better weather prediction. It features two characteristics. First it is huge in size with 2D spatial coverage and high spectral resolution in the infrared region. Second it allows low tolerance of noise and error in retrieving the geophysical parameters where a mathematically ill-posed problem is involved. Therefore compression is better to be lossless or near lossless for data transfer and archive. Meanwhile medical data from X-ray computerized tomography (CT) or magnetic resonance imaging (MRI) techniques also possesses similar characteristics. It provides motivation to apply lossless compression schemes for medical data to the hyperspectral sounder data. In this paper, we explore the use of a wavelet-based lossless data compression scheme for the 3D hyperspectral data which uses in sequence a forward difference scheme, an integer wavelet transform, a Burrows-Wheeler transform and an arithmetic coder. Compared to previous work, our approach is shown to outperform the CALIC and 3D EZW schemes.

Paper Details

Date Published: 14 October 2004
PDF: 10 pages
Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); doi: 10.1117/12.560527
Show Author Affiliations
Shih-Chieh Wei, Tamkang Univ. (Taiwan)
Bormin Huang, Univ. of Wisconsin/Madison (United States)


Published in SPIE Proceedings Vol. 5548:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective
Hung-Lung Allen Huang; Hal J. Bloom, Editor(s)

© SPIE. Terms of Use
Back to Top