@inproceedings{51f6e019b1be477384c12feb71fe35ef,
title = "An adaptive 3D de-noising algorithm of low snr video in stationary scenes",
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.",
keywords = "3D de-noising, Background difference, DSP, Low SNR video",
author = "Xu Chao and Qin Shan and Ren Jun and Li Zhoukui",
year = "2013",
doi = "10.1117/12.2037185",
language = "English",
isbn = "9780819499639",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "2013 International Conference on Optical Instruments and Technology",
note = "2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2013 ; Conference date: 17-11-2013 Through 19-11-2013",
}