An adaptive 3D de-noising algorithm of low SNR video in stationary scenes

Chao Xu; Shan Qin; Jun Ren; Zhoukui Li

doi:10.1117/12.2037185

19 December 2013 An adaptive 3D de-noising algorithm of low SNR video in stationary scenes

Chao Xu, Shan Qin, Jun Ren, Zhoukui Li

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 90450U (2013) https://doi.org/10.1117/12.2037185
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

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.

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Chao Xu, Shan Qin, Jun Ren, and Zhoukui Li "An adaptive 3D de-noising algorithm of low SNR video in stationary scenes", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 90450U (19 December 2013); https://doi.org/10.1117/12.2037185

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KEYWORDS

Video

Signal to noise ratio

Digital signal processing

Video processing

Detection and tracking algorithms

Spatial filters

Digital filtering

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