16 September 2011 Lossless compression of 3D Aurora images using adaptive-context-based prediction modeling in China's Arctic Yellow River Station
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Abstract
The researching on aurora images is playing an important role in scientific and living fields. However, the aurora images have to face the problems of transmission and storage in China's Arctic station. This paper proposes a lossless compression algorithm aiming at the long distance transmission of aurora images for real-time requirement. The special correlation characters of 3D aurora images are discussed firstly, and then an adaptive context-based prediction algorithm is proposed. The proposed algorithm can effectively reduce inter-frame and intra-frame correlations according to the characteristics of 3D aurora images using our proposed prediction modeling. Compared with the state-of-art algorithms, the proposed algorithm not only can achieve better compression performance, but also satisfy the complexity requirement.
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Jiaji Wu, Jiaji Wu, Tao Teng, Tao Teng, LC Jiao, LC Jiao, "Lossless compression of 3D Aurora images using adaptive-context-based prediction modeling in China's Arctic Yellow River Station", Proc. SPIE 8157, Satellite Data Compression, Communications, and Processing VII, 81570J (16 September 2011); doi: 10.1117/12.893011; https://doi.org/10.1117/12.893011
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