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
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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