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Mathematical Problems in Engineering
Volume 2014, Article ID 964835, 6 pages
Research Article

Image Recovery Algorithm Based on Learned Dictionary

College of Information Science & Technology, Hunan Agricultural University, Changsha 410128, China

Received 28 May 2014; Accepted 25 July 2014; Published 12 August 2014

Academic Editor: Binxiang Dai

Copyright © 2014 Xinghui Zhu and Fang Kui. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We proposed a recovery scheme for image deblurring. The scheme is under the framework of sparse representation and it has three main contributions. Firstly, considering the sparse property of natural image, the nonlocal overcompleted dictionaries are learned for image patches in our scheme. And, then, we coded the patches in each nonlocal clustering with the corresponding learned dictionary to recover the whole latent image. In addition, for some practical applications, we also proposed a method to evaluate the blur kernel to make the algorithm usable in blind image recovery. The experimental results demonstrated that the proposed scheme is competitive with some current state-of-the-art methods.