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.

Date Published: 25 October 2004
PDF: 7 pages
Proc. SPIE 5600, Multimedia Systems and Applications VII, (25 October 2004);

Published in SPIE Proceedings Vol. 5600:
Multimedia Systems and Applications VII
Chang Wen Chen; C.-C. Jay Kuo; Anthony Vetro, Editor(s)