Paper
20 October 2015 A lossless compression algorithm for aurora spectral data using online regression prediction
Author Affiliations +
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Auroras

Image compression

Spectrographs

Atmospheric particles

Digital filtering

Filtering (signal processing)

Hyperspectral imaging

Back to Top