AllFocus: Patch-Based Video Out-of-Focus Blur Reconstruction

被引:15
|
作者
Wang, Yinting [1 ]
Wang, Zhenyang [1 ]
Tao, Dapeng [2 ]
Zhuo, Shaojie [3 ]
Xu, Xianghua [4 ]
Pu, Shiliang [5 ]
Song, Mingli [1 ]
机构
[1] Zhejiang Univ, Coll Comp Sci & Technol, Zhejiang Prov Key Lab Serv Robot, Hangzhou 310027, Zhejiang, Peoples R China
[2] Yunnan Univ, Sch Informat Sci & Engn, Kunming 650091, Yunnan, Peoples R China
[3] Qualcomm Canada Inc, Thornhill, ON L3T 7W3, Canada
[4] Hangzhou Dianzi Univ, Sch Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China
[5] HikVis Technol, Res Inst, Hangzhou 310012, Zhejiang, Peoples R China
基金
美国国家科学基金会;
关键词
Out-of-focus blur; patch tracking; sharpness; IMAGES;
D O I
10.1109/TCSVT.2016.2555740
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Amateur videos always contain focusing issues. A focusing mistake may produce out-of-focus blur, which seriously degrades the expressive force of the video. In this paper, we propose a patch-based method to remove the out-of-focus blur of a video and build an all-in-focus video. We assume that the out-of-focus blurry region in one frame will be clear in a portion of other frames; thus, the clear corresponding regions can be used to reconstruct the blurry one. We divide each video frame into a grid of patches and track each patch in the surrounding frames. We independently reconstruct each video frame by building a Markov random field model to identify the optimal target patches that are sharp, similar to the original patches, and are coherent with their neighboring patches within the overlapped regions. To recover an all-in-focus video, an iterative framework is utilized, in which the reconstructed video of each iteration is substituted in the next iteration. Finally, we employ the idea of a bilateral filter to temporally smooth the reconstructed video. The experimental results and the comparison with the previous works demonstrate the effectiveness of our method.
引用
收藏
页码:1895 / 1908
页数:14
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