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Proceedings Paper

A lossless compression algorithm for aurora spectral data using online regression prediction
Author(s): Wanqiu Kong; Jiaji Wu
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Paper Abstract

Lossless compression algorithms are available for preservation of aurora images. Handling with aurora image compression, linear prediction based method has outstanding compression performance. However, this performance is limited by prediction order and time complexity of linear prediction is relatively high. This paper describes how to solve the conflict between high prediction order and low compression bit rate with an online linear regression with RLS (OLRRLS) algorithm. Experiment results show that OLR-RLS achieves average 7%~11.8% improvement in compression gain and 2.8x speed up in computation time over linear prediction.

Paper Details

Date Published: 20 October 2015
PDF: 12 pages
Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 964611 (20 October 2015); doi: 10.1117/12.2199209
Show Author Affiliations
Wanqiu Kong, Xidian Univ. (China)
Jiaji Wu, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 9646:
High-Performance Computing in Remote Sensing V
Bormin Huang; Sebastián López; Zhensen Wu; Jose M. Nascimento; Boris A. Alpatov; Jordi Portell de Mora, Editor(s)

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