One-parameter l1 Prior in Variational Bayesian Super resolution
文献类型：会议论文
| 作者 | Min Lei [1,2,3,4], Yang Ping [1,3], Liu Wenjin [1,3], Luan Yinsen [1,3], Xu Bing [1,3], Liu Yong [2] |
| 出版日期 | 2017 |
| 关键词 | super resolution prior model variational Bayesian Kullback-Leibler distance |
| 卷号 | 10462 |
| 页码 | 104622Z |
| 英文摘要 | In this paper, we address the multiframe super resolution problem from a set of degraded, under-sampled, shifted and rotated low resolution images to obtain a high resolution image using the variational Bayesian methods. In the Bayesian framework a prior model on the high resolution image need to be specified, its aim is to summarize our knowledge of the image and to constraint the ill-posed image reconstruction problem. Appropriate prior model selection according to the super resolution scenario is a critical issue. Here we propose the one-parameter l1 prior. Experimental results demonstrate that the proposed method is very effective and compared favorably to state-of-the-art super resolution algorithms. |
| 会议录 | 0277-786X
 |
| 语种 | 英语 |
| 源URL | [http://ir.ioe.ac.cn/handle/181551/9023]  |
| 专题 | 光电技术研究所_自适应光学技术研究室（八室） |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100039, China 2.The Institute of Optics and Electronics the Chinese Academy of Sciences, Chengdu 610209, China 3.School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu 610054, China 4.Key Laboratory on Adaptive Optics, Chinese Academy of Sciences , Chengdu, China 610209 |
| 推荐引用方式 GB/T 7714 | Min Lei [1,2,3,4], Yang Ping [1,3], Liu Wenjin [1,3], Luan Yinsen [1,3], Xu Bing [1,3], Liu Yong [2]. One-parameter l1 Prior in Variational Bayesian Super resolution[C]. 见:. |
入库方式： OAI收割
来源：光电技术研究所
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