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.
Lossless compression for aurora spectral images using fast online bi-dimensional decorrelation method / W. Kong, J. Wu, Z. Hu, M. Anisetti, E. Damiani, G. Jeon. - In: INFORMATION SCIENCES. - ISSN 0020-0255. - 381(2017), pp. 33-45. [10.1016/j.ins.2016.11.008]
Lossless compression for aurora spectral images using fast online bi-dimensional decorrelation method
M. Anisetti;E. DamianiPenultimo
;
2017
Abstract
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.File | Dimensione | Formato | |
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