[1]刘 梓,宋晓宁,於东军,等.基于多成分字典和稀疏表示的超分辨率重建算法[J].南京理工大学学报(自然科学版),2014,38(01):1-5.
 Liu Zi,Song Xiaoning,Yu Dongjun,et al.Super-resolution reconstruction algorithm based on multi-component dictionary and sparse representation[J].Journal of Nanjing University of Science and Technology,2014,38(01):1-5.
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基于多成分字典和稀疏表示的超分辨率重建算法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
38卷
期数:
2014年01期
页码:
1-5
栏目:
出版日期:
2014-02-28

文章信息/Info

Title:
Super-resolution reconstruction algorithm based on multi-component dictionary and sparse representation
作者:
刘 梓宋晓宁於东军唐振民
南京理工大学 计算机科学与工程学院,江苏 南京 210094
Author(s):
Liu ZiSong XiaoningYu DongjunTang Zhenmin
School of Computer Science and Engineering,NUST,Nanjing 210094,China
关键词:
超分辨率 稀疏表示 多成分字典
Keywords:
super-resolution sparse representation multi-component dictionary
分类号:
TP391.41
摘要:
为了解决单幅图像超分辨重建的问题,该文提出了一种在稀疏表示理论框架下基于多成分字典的方法。首先根据图像的退化模型,深入分析高低分辨率图像的关系,得到高分辨图像可由低分辨率图像在对应字典下的稀疏系数来重构的结论。根据这一结论,采用多成分字典分别表示图像的不同结构特征,并用匹配追踪的方法得到低分辨图像在多成分字典下的表示系数,然后在对应的高分辨字典下对高分辨率的图像进行重建,实现了基于多成分字典的单幅图像超分辨率重建。该文所提的方法对单幅图像的超分辨率重建具有较好的通用性,相对于传统的超分辨重建算法,在自然图像和卡通图像的实验中验证了算法的有效性。
Abstract:
In order to solve the problem of super-resolution reconstruction of single image,a hybrid approach is presented under the framework of sparse representation with multi-component dictionary.According to the image degradation model,the algorithms focus on the relationship between the low-resolution images and high-resolution images.This paper concludes that the high-resolution images can be reconstructed by the coefficients of low-resolution images in the corresponding dictionary.The sparse coefficients are obtained by the method of match pursuit based on the multi-component dictionary which indicates different structural characteristics of the image.The high-resolution images are reconstructed in the corresponding high-resolution dictionary.This paper introduces an objective and new strategy capable of efficiently guiding the image restoration.Extensive experimental studies conducted on the nature and cartoon images show the effectiveness of the proposed method.

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备注/Memo

备注/Memo:
收稿日期:2012-07-05 修回日期:2012-07-25
基金项目:国家自然科学基金(90820306); 江苏省自然科学基金(BK2011492); 中国博士后科学基金(2011M500926); 江苏省博士后科学基金(1102063C)
作者简介:刘梓(1985-),男,博士生,主要研究方向:模式识别与智能系统,图像识别,计算机视觉,E-mail:sandylaublue@163.com。
引文格式:刘梓,宋晓宁,於东军,等.基于多成分字典和稀疏表示的超分辨率重建算法[J].南京理工大学学报,2014,38(1):1-5.
投稿网址:http://njlgdxxb.paperonce.org
更新日期/Last Update: 2014-02-28