25 October 2004 Scalable object-based compression algorithm for segmented space-telescope images
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Proceedings Volume 5600, Multimedia Systems and Applications VII; (2004) https://doi.org/10.1117/12.571475
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
Abstract
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.
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Helen Boussalis, Helen Boussalis, Charles Liu, Charles Liu, Khosrow Rad, Khosrow Rad, Jianyu Dong, Jianyu Dong, "Scalable object-based compression algorithm for segmented space-telescope images", Proc. SPIE 5600, Multimedia Systems and Applications VII, (25 October 2004); doi: 10.1117/12.571475; https://doi.org/10.1117/12.571475
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