背景提取与前景滤波相结合的时空联合视频降噪
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航空光学成像与测量技术研究部中国科学院长春光学精密机械与物理研究所长春130033

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TN911.81

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吉林省科技发展计划(20126016)项目


Spatiotemporal combination method for video denoising with the combing of background extraction and foreground filtering
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Research Department of Airborne Optical Imaging and Measurement Technology, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

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    摘要:

    针对视频图像的高斯型随机噪声,提出一种背景提取与前景滤波相结合的时空联合视频降噪算法。结合图像膨胀处理和背景差分法将视频图像分为背景和前景部分,前景部分和背景部分分别采用基于Nonlocal means filter的时空联合视频降噪算法和时域平均算法进行降噪处理,并将处理之后的前景和背景相加,得到最终的视频图像序列。最后,给出了Nonlocal means filter方法和本文降噪方法降噪效果的对比试验。实验结果表明,Nonlocal means filter和本文降噪方法降噪后2个测试序列的PSNR分别为33.0043、29.0365和35.8340、31.5261。这说明对于背景固定的监控类视频,该算法在降低算法复杂度、提高实时性的基础上,有效的处理和保留了视频图像的低频信息和高频细节。

    Abstract:

    To solve the random gauss noise in the video, this paper proposed a spatiotemporal combination method with the combing of background extraction and foreground filtering. Video images in this paper are divided into two parts: The foreground and the background, using background difference method combined with image expanding. Then deal with the two parts using spatiotemporal combination method based on the Nonlocal means filter and direct meaning in time domain. And then the output video can be got by adding the foreground and the background which are proposed. At last, this paper give the comparison of the Nonlocal means filter and the method in this paper. Experimental results indicate that the PSNR of the tow test video after denoising reaches 33.0043、29.0365 and 35.8340、31.5261. Experiment shows that for the monitoring video with fixed background, the arithmetic in this paper effectively deal with the lowfrequency information and the highfrequency details, on the basis of reducing the complexity and improving the realtime ability of the method.

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周占民.背景提取与前景滤波相结合的时空联合视频降噪[J].电子测量技术,2015,38(6):68-72

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  • 在线发布日期: 2016-05-27
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