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

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• 作者：Wanqiu Kong^a ; ^{wanqiukong@stu.xidian.edu.cn} ; Jiaji Wu^a ; ^{wujj@mail.xidian.edu.cn} ; Zejun Hu^b ; ^{huzejun@pric.org.cn} ; Marco Anisetti^c ; ^{marco.anisetti@unimi.it} ; Ernesto Damiani^c ; ^d ; ^{ernesto.damiani@kustar.ac.ae} ; Gwanggil Jeon ; ^a ; ^e ; ^{ggjeon@gmail.com}
• 关键词：Lossless compression ; Aurora spectral images ; Online ; Bi-dimensional decorrelation ; Parallel
• 刊名：Information Sciences
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：381
• 期：Complete
• 页码：33-45
• 全文大小：1928 K
• 卷排序：381

文摘

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.