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Paper: Sparse Expression: A Case of Radio Astronomy Image Compression
Volume: 512, Astronomical Data Analysis Software and Systems XXV
Page: 185
Authors: Wang, Y.; Gao, G.; Wu, D.; Yu, X.; Tian, W.
Abstract: With radio astronomy data exploding, lossless compression, one existing astronomical image data compression algorithms, can guarantee to restore the image without distortion, but the compression ratio is too low, and it has brought great challenge to the radio astronomy image storage and transmission. In view of this situation, this paper proposes a sparse expression astronomical image compression algorithm. The algorithm uses the K-SVD algorithm to get KSVD dictionary through a complete DCT atoms library updates adaptively, and representing the astronomical data sparsely using the dictionary, then compressing sparse coefficient obtained by improved run-length algorithm coded and stored as a binary stream. Experiments show that for FITS format radio astronomy data processing, when the compression ratio is 5:1, the difference between raw data and the decompressed data after a lossy compression is minimal, the mean square error is from 0.0026 to 0.0337, it will not affect interpreting of the very weak information of the data.
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