Deep Maximum a Posterior Estimator for Video Denoising

Author(s):  
Lu Sun ◽  
Weisheng Dong ◽  
Xin Li ◽  
Jinjian Wu ◽  
Leida Li ◽  
...  
2011 ◽  
Vol 31 (5) ◽  
pp. 1209-1213
Author(s):  
Hong-yan ZHANG ◽  
Huan-feng SHEN ◽  
Liang-pei ZHANG ◽  
Ping-xiang LI ◽  
Qiang-qiang YUAN

2020 ◽  
pp. 1-11
Author(s):  
Shufang Li ◽  
Wang Juan

For the English classroom teaching video denoising algorithm, it is not only necessary to consider whether the noise removal of the output video is thorough, but also to consider the actual operating efficiency and robustness of the algorithm. In the process of the thesis research, after reading a large number of internal and external documents on video denoising algorithms and analyzing the pros and cons of various denoising algorithms, this paper proposes a new video denoising algorithm, which uses the recently proposed grid flow motion model based on camera motion compensation to generate denoised video. Compared with the current advanced video denoising schemes, our method processes noisy frames faster and has good robustness. In addition, this article improves the algorithm framework so that the algorithm can not only deal with offline video denoising, but also deal with online video denoising.


2016 ◽  
Vol 25 (6) ◽  
pp. 2573-2586 ◽  
Author(s):  
Antoni Buades ◽  
Jose-Luis Lisani ◽  
Marko Miladinovic

Author(s):  
Zhihang Ren ◽  
Jiajia Li ◽  
Shuaicheng Liu ◽  
Bing Zeng
Keyword(s):  

2018 ◽  
Vol 25 (7) ◽  
pp. 1009-1013 ◽  
Author(s):  
Han Guo ◽  
Namrata Vaswani
Keyword(s):  

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