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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yunhai Liu Baolei Xie Heyi Guo Xiaochen Quan Shengtian Yang |
| Copyright Year | 2008 |
| Description | Author affiliation: Inst. of Inf. & Commun. Eng., Zhejiang Univ., Hangzhou (Yunhai Liu; Baolei Xie; Heyi Guo; Xiaochen Quan; Shengtian Yang) |
| Abstract | Because of the characteristics of photoelectric sensors and the working environment of cameras, real-time surveillance video contains much noise, which does not only decrease the subjective visual quality, but also increases the output bitrate of video encoder. The effect of partial spatio-temporal smoothing is not evident. According to the characteristics of surveillance video, we propose a novel algorithm based on video content, setting up adaptive background models to accomplish foreground segmentation, reducing background noise via model parameters and foreground noise via 3D median filter. To the sequences of "hall_monitor" polluted with Gaussian or Poisson noise, the results show that the new algorithm increases PSNR about 8 dB, and saves over 90% of encoder output bitrate. |
| Starting Page | 1127 |
| Ending Page | 1131 |
| File Size | 6201082 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424423736 |
| DOI | 10.1109/CHINACOM.2008.4685224 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-08-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | PSNR Smoothing methods Noise reduction Adaptive filters Sensor phenomena and characterization background models Background noise Surveillance Working environment noise Bit rate Cameras segmentation 3D median filter surveillance video denoising |
| Content Type | Text |
| Resource Type | Article |
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