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Proceedings Paper

Analysis the application of several denoising algorithm in the astronomical image denoising
Author(s): Chao Jiang; Ze-xun Geng; Yong-qiang Bao; Xiao-feng Wei; Ying-feng Pan
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Paper Abstract

Image denoising is an important method of preprocessing, it is one of the forelands in the field of Computer Graphic and Computer Vision. Astronomical target imaging are most vulnerable to atmospheric turbulence and noise interference, in order to reconstruct the high quality image of the target, we need to restore the high frequency signal of image, but noise also belongs to the high frequency signal, so there will be noise amplification in the reconstruction process. In order to avoid this phenomenon, join image denoising in the process of reconstruction is a feasible solution. This paper mainly research on the principle of four classic denoising algorithm, which are TV, BLS - GSM, NLM and BM3D, we use simulate data for image denoising to analysis the performance of the four algorithms, experiments demonstrate that the four algorithms can remove the noise, the BM3D algorithm not only have high quality of denosing, but also have the highest efficiency at the same time.

Paper Details

Date Published: 21 February 2014
PDF: 7 pages
Proc. SPIE 9142, Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics: Optical Imaging, Remote Sensing, and Laser-Matter Interaction 2013, 91421N (21 February 2014); doi: 10.1117/12.2054427
Show Author Affiliations
Chao Jiang, Information Engineering Univ. (China)
Ze-xun Geng, Information Engineering Univ. (China)
Yong-qiang Bao, Information Engineering Univ. (China)
Troops 66393 (China)
Xiao-feng Wei, Information Engineering Univ. (China)
Ying-feng Pan, Troops 61175 (China)


Published in SPIE Proceedings Vol. 9142:
Selected Papers from Conferences of the Photoelectronic Technology Committee of the Chinese Society of Astronautics: Optical Imaging, Remote Sensing, and Laser-Matter Interaction 2013
Jorge Ojeda-Castaneda; Shensheng Han; Ping Jia; Jiancheng Fang; Dianyuan Fan; Liejia Qian; Yuqiu Gu; Xueqing Yan, Editor(s)

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