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Proceedings Paper

An adaptive 3D de-noising algorithm of low SNR video in stationary scenes
Author(s): Chao Xu; Shan Qin; Jun Ren; Zhoukui Li
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Paper Abstract

As one of the monitoring modes, video monitoring in stationary scenes is widely used nowadays. To improve video SNR(signal to noise ratio) in stationary scenes, an adaptive 3D de-noising scheme based on background subtraction algorithm and blocks judgment method was presented. The multi-frame-average method based on inter-frame difference was applied to estimate the background. The weighted average value of the average frame and the original background frame is used to update the background,and the temporal filtering will be completed while updating background. The moving pixels are detected using background difference algorithm firstly and judged again with blocks judgment method. The proposed algorithm is implemented on the DSP platform. Experimental results of low SNR video show that the noise is reduced obviously, the majority of edges and details are retained simultaneously avoiding ghosting, thus achieving a significant improvement in video quality.

Paper Details

Date Published: 19 December 2013
PDF: 12 pages
Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90450U (19 December 2013); doi: 10.1117/12.2037185
Show Author Affiliations
Chao Xu, Beijing Institute of Technology (China)
Shan Qin, Beijing Institute of Technology (China)
Jun Ren, Beijing Institute of Technology (China)
Zhoukui Li, Science and Technology on Low-Light-Level Night Vision Lab. (China)


Published in SPIE Proceedings Vol. 9045:
2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology
Xinggang Lin; Jesse Zheng, Editor(s)

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