Computer Science – Multimedia
Scientific paper
Oct 2004
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004spie.5600..231b&link_type=abstract
Multimedia Systems and Applications VII. Edited by Chen, Chang Wen; Kuo, C.-C. Jay; Vetro, Anthony. Proceedings of the SPIE, Vo
Computer Science
Multimedia
Scientific paper
The noise-alike nature of astronomical images imposes a great challenge on compression. Due to the lack of correlation among adjacent pixels, it is very difficult to achieve good compression result using standard algorithms. To address the above challenge, a novel object-based compression method is proposed in this paper. Based on object analysis, the astronomical entities presented in the image are classified into two categories: clear and faint objects. For the former, a zerotree based wavelet compression algorithm is employed to achieve scalable coding; for the latter, a predictive coding method is used to preserve their location and intensity. The objective is to enhance the detection of faint object in astronomical images while providing a good overall visual effect. Experiment results demonstrate the superior performance of our proposed algorithm.
Boussalis Helen
Dong Jianyu
Liu Charles
Rad Khosrow
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