Infrared image de-noising based on K-SVD over-complete dictionaries learning | |
Bin Shan; Wei Hao(郝伟); Rui Zhao | |
2012 | |
会议名称 | 2012 5th International Congress on Image and Signal Processing, CISP 2012 |
会议录名称 | 2012 5th International Congress on Image and Signal Processing, CISP 2012 |
页码 | 316-320 |
会议日期 | October 16, 2012 - October 18, 2012 |
会议地点 | Chongqing, China |
出版地 | 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States |
出版者 | IEEE Computer Society |
产权排序 | 1 |
摘要 | The sparse representation of image based on over-complete dictionaries is a new image representation theory. Using the redundancy of over-complete dictionaries can effectively capture the various structure detail characteristics of an image, so as to realize the efficient representation of the image. In this paper we propose an infrared image de-noising algorithm based on K-SVD over-complete dictionaries learning using the over-complete dictionary image sparse representation theory. The experimental results compared with the common de-noising algorithm processing results prove the effectiveness of the proposed method. |
收录类别 | EI |
ISBN号 | 9781467309622 |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/20805 |
专题 | 光电跟踪与测量技术研究室 |
推荐引用方式 GB/T 7714 | Bin Shan,Wei Hao,Rui Zhao. Infrared image de-noising based on K-SVD over-complete dictionaries learning[C]. 2001 L Street N.W., Suite 700, Washington, DC 20036-4928, United States:IEEE Computer Society,2012:316-320. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Infrared image de-no(491KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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