Lossless compression for aurora spectral images using fast online bi-dimensional decorrelation method

In this paper, we propose a lossless compression method to resolve the limitations in the real-time transmission of aurora spectral images. This method bi-dimensionally decorrelates the spatial and spectral domains and effectively removes side information of recursively computed coefficients to achi...

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Bibliographic Details
Published in:Information Sciences
Main Authors: W. Kong, J. Wu, Z. Hu, G. Jeon, M. Anisetti, E. Damiani
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2017
Subjects:
Aurora spectral image
Bi-dimensional decorrelation
Lossless compression
Online
Parallel
Control and Systems Engineering
Theoretical Computer Science
Software
Computer Science Application
Computer Vision and Pattern Recognition
Information Systems and Management
Artificial Intelligence
Settore INF/01 - Informatica
Antarc*
Antarctic
Online Access:http://hdl.handle.net/2434/470640
https://doi.org/10.1016/j.ins.2016.11.008
Description
Summary:In this paper, we propose a lossless compression method to resolve the limitations in the real-time transmission of aurora spectral images. This method bi-dimensionally decorrelates the spatial and spectral domains and effectively removes side information of recursively computed coefficients to achieve high quality rapid compression. Experiments on data sets captured from the Antarctic Zhongshan Station show that the proposed algorithm can meet real-time requirements by using parallel processing to achieve outstanding compression ratio performance with low computational complexity.

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