@inproceedings{1469805f993c450c89157e282a203f4f,
title = "Exploiting structured sparsity for image deblurring",
abstract = "Sparsity is an ubiquitous property exhibited by many natural real-world data such as images, which has been playing an important role in image and multi-media data processing. However, for many data, such as images, the sparsity pattern is not completely random, i.e., there are structures over the sparse coefficients. By exploiting this structure, we can model the data better and may further improve the performance of the recovery algorithm. In this paper, we exploit the structured sparsity of natural images for image deblurring application. Experimental results clearly demonstrate the effectiveness of the proposed approach.",
keywords = "image deblurring, image restoration, signal processing, structured sparsity",
author = "Haichao Zhang and Yanning Zhang and Huang, \{Thomas S.\}",
year = "2012",
doi = "10.1109/ICME.2012.110",
language = "英语",
isbn = "9781467316590",
series = "Proceedings - IEEE International Conference on Multimedia and Expo",
publisher = "IEEE Computer Society",
pages = "616--621",
booktitle = "Proceedings - 2012 IEEE International Conference on Multimedia and Expo, ICME 2012",
note = "13th IEEE International Conference on Multimedia and Expo, ICME 2012 ; Conference date: 09-07-2012 Through 13-07-2012",
}