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Medical image fusion based on NSCT and sparse representation
Shen, Chao1,2; Gao, Wei1; Ma, Caiwen1; Song, Zongxi1; Yin, Fei2; Dan, Lijun1; Wang, Fengtao1
2018
会议名称10th International Conference on Digital Image Processing, ICDIP 2018
会议录名称Tenth International Conference on Digital Image Processing, ICDIP 2018
卷号10806
会议日期2018-05-11
会议地点Shanghai, China
出版者SPIE
产权排序1
摘要Image fusion is to get a fused image that contains all important information from source images of the same scene. Meanwhile, multi-scale transforms and sparse representation (SR) are the two most effective techniques for image fusion. However, the SR-based image fusion methods are time-consuming and do not take the structural information of the source images into consideration. In addition, different multi-scale transform-based methods have their inevitable defects waiting to be solved till now. Therefore, in this paper, a new image fusion method combining nonsubsampled contourlet transform (NSCT) with SR is proposed. A decision map for the low-frequency coefficients according to the high-frequency coefficients is made to overcome these problems. Furthermore, it can reduce the calculation cost of the fusion algorithm and retain the useful information of source images as far as possible. Comparing with conventional multi-scale transform based methods and sparse representation based methods with a fixed or learned dictionary, the proposed method has better fusion performance in the field of medical image fusion. © 2018 SPIE.
作者部门空间光学应用研究室
DOI10.1117/12.2503126
收录类别EI
ISBN号9781510621992
语种英语
ISSN号0277786X
EI入藏号20183605779292
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30611
专题空间光学应用研究室
通讯作者Gao, Wei
作者单位1.Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an; 710071, China;
2.University of Chinese Academy of Science, Beijing; 100049, China
推荐引用方式
GB/T 7714
Shen, Chao,Gao, Wei,Ma, Caiwen,et al. Medical image fusion based on NSCT and sparse representation[C]:SPIE,2018.
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