Please use this identifier to cite or link to this item: https://doi.org/10.1109/CVPRW.2009.5206711
Title: High-quality curvelet-based motion deblurring from an image pair
Authors: Cai, J.-F. 
Ji, H. 
Liu, C. 
Shen, Z. 
Issue Date: 2009
Citation: Cai, J.-F.,Ji, H.,Liu, C.,Shen, Z. (2009). High-quality curvelet-based motion deblurring from an image pair. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009 : 1566-1573. ScholarBank@NUS Repository. https://doi.org/10.1109/CVPRW.2009.5206711
Abstract: One promising approach to remove motion deblurring is to recover one clear image using an image pair. Existing dual-image methods require an accurate image alignment between the image pair, which could be very challenging even with the help of user interactions. Based on the observation that typical motion-blur kernels will have an extremely sparse representation in the redundant curvelet system, we propose a new minimization model to recover a clear image from the blurred image pair by enhancing the sparsity of blur kernels in the curvelet system. The sparsity prior on the motion-blur kernels improves the robustness of our algorithm to image alignment errors and image formation noise. Also, a numerical method is presented to efficiently solve the resulted minimization problem. The experiments showed that our proposed algorithm is capable of accurately estimating the blur kernels of complex camera motions with low requirement on the accuracy of image alignment, which in turn led to a high-quality recovered image from the blurred image pair. ©2009 IEEE.
Source Title: 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
URI: http://scholarbank.nus.edu.sg/handle/10635/115434
ISBN: 9781424439935
DOI: 10.1109/CVPRW.2009.5206711
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