Please use this identifier to cite or link to this item:
|Title:||Framelet-based blind motion deblurring from a single image|
split Bregman method
|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. https://doi.org/10.1109/TIP.2011.2164413|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jun 15, 2018
WEB OF SCIENCETM
checked on May 22, 2018
checked on May 11, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.