OPT OpenIR  > 光电跟踪与测量技术研究室
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
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Bin Shan]的文章
[Wei Hao(郝伟)]的文章
[Rui Zhao]的文章
百度学术
百度学术中相似的文章
[Bin Shan]的文章
[Wei Hao(郝伟)]的文章
[Rui Zhao]的文章
必应学术
必应学术中相似的文章
[Bin Shan]的文章
[Wei Hao(郝伟)]的文章
[Rui Zhao]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。