A lossless compression algorithm for aurora spectral data using online regression prediction

Wanqiu Kong; Jiaji Wu

doi:10.1117/12.2199209

20 October 2015 A lossless compression algorithm for aurora spectral data using online regression prediction

Wanqiu Kong, Jiaji Wu

Author Affiliations +

Proceedings Volume 9646, High-Performance Computing in Remote Sensing V; 964611 (2015) https://doi.org/10.1117/12.2199209
Event: SPIE Remote Sensing, 2015, Toulouse, France

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.

Citation Download Citation

Wanqiu Kong and Jiaji Wu "A lossless compression algorithm for aurora spectral data using online regression prediction", Proc. SPIE 9646, High-Performance Computing in Remote Sensing V, 964611 (20 October 2015); https://doi.org/10.1117/12.2199209

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