UM
Temporal Coherence-Based Deblurring Using Non-Uniform Motion Optimization
Congbin Qiao1; Rynson W. H. Lau2; Bin Sheng1; Benxuan Zhang1; Enhua Wu3
2017-10-01
Source PublicationIEEE Transactions on Image Processing
ISSN10577149
Volume26Issue:10Pages:4991-5004
Abstract

Non-uniform motion blur due to object movement or camera jitter is a common phenomenon in videos. However, the state-of-the-art video deblurring methods used to deal with this problem can introduce artifacts, and may sometimes fail to handle motion blur due to the movements of the object or the camera. In this paper, we propose a non-uniform motion model to deblur video frames. The proposed method is based on superpixel matching in the video sequence to reconstruct sharp frames from blurry ones. To identify a suitable sharp superpixel to replace a blurry one, we enrich the search space with a non-uniform motion blur kernel, and use a generalized PatchMatch algorithm to handle rotation, scale, and blur differences in the matching step. Instead of using pixel-based or regular patch-based representation, we adopt a superpixel-based representation, and use color and motion to gather similar pixels. Our non-uniform motion blur kernels are estimated from the motion field of these superpixels, and our spatially varying motion model considers spatial and temporal coherence to find sharp superpixels. Experimental results showed that the proposed method can reconstruct sharp video frames from blurred frames caused by complex object and camera movements, and performs better than the state-of-the-art methods.

KeywordImage Deblurring Non-uniform Blur Kernel Video Deblurring Video Processing
DOIhttp://doi.org/10.1109/TIP.2017.2731206
URLView the original
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Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2.Department of Computer Science and Engineering, the City University of Hong Kong, Hong Kong.
3.Institute of Software, Chinese Academy of Sciences, Beijing 100190, China.
Recommended Citation
GB/T 7714
Congbin Qiao,Rynson W. H. Lau,Bin Sheng,et al. Temporal Coherence-Based Deblurring Using Non-Uniform Motion Optimization[J]. IEEE Transactions on Image Processing,2017,26(10):4991-5004.
APA Congbin Qiao,Rynson W. H. Lau,Bin Sheng,Benxuan Zhang,&Enhua Wu.(2017).Temporal Coherence-Based Deblurring Using Non-Uniform Motion Optimization.IEEE Transactions on Image Processing,26(10),4991-5004.
MLA Congbin Qiao,et al."Temporal Coherence-Based Deblurring Using Non-Uniform Motion Optimization".IEEE Transactions on Image Processing 26.10(2017):4991-5004.
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