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Title: Framelet-based blind motion deblurring from a single image
Authors: Cai, J.-F.
Ji, H. 
Liu, C. 
Shen, Z. 
Keywords: Blind deconvolution
motion blur
split Bregman method
tight frame
Issue Date: Feb-2012
Citation: Cai, J.-F., Ji, H., Liu, C., Shen, Z. (2012-02). Framelet-based blind motion deblurring from a single image. IEEE Transactions on Image Processing 21 (2) : 562-572. ScholarBank@NUS Repository.
Abstract: How to recover a clear image from a single motion-blurred image has long been a challenging open problem in digital imaging. In this paper, we focus on how to recover a motion-blurred image due to camera shake. A regularization-based approach is proposed to remove motion blurring from the image by regularizing the sparsity of both the original image and the motion-blur kernel under tight wavelet frame systems. Furthermore, an adapted version of the split Bregman method is proposed to efficiently solve the resulting minimization problem. The experiments on both synthesized images and real images show that our algorithm can effectively remove complex motion blurring from natural images without requiring any prior information of the motion-blur kernel. © 2011 IEEE.
Source Title: IEEE Transactions on Image Processing
ISSN: 10577149
DOI: 10.1109/TIP.2011.2164413
Appears in Collections:Staff Publications

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