OPT OpenIR  > 光电跟踪与测量技术研究室
Fusion method of multispectral and panchromatic images based on NSST and improved PCNN
Song, Chong1,2; Zeng, Litang3; Jiang, Kai1; Liu, Zhaohui1; Zhou, Liang1
2021
会议名称2021 International Conference on Optics and Image Processing, ICOIP 2021
会议录名称International Conference on Optics and Image Processing, ICOIP 2021
卷号11915
会议日期2021-06-04
会议地点Guilin, China
出版者SPIE
产权排序1
摘要

The dual-camera coded aperture snapshot spectral imager(DC-CASSI) includes the coded aperture snapshot spectral imager(CASSI) and panchromatic imager. CASSI can obtain the three-dimensional spectral image information of the target in a single coding within a single integral time, but it is difficult to achieve high-quality reconstruction of spectral image in a single coding. Therefore, the panchromatic image acquired by the panchromatic imager should be fused with it to obtain high-quality multispectral reconstruction images. Based on the imaging characteristics of DC-CASSI, a multispectral and panchromatic image fusion algorithm based on Non-subsampled Shearlets Transform (NSST) and improved Pulse Coupled Neural Network(PCNN) is proposed. The fusion experimental results show that compared with other traditional fusion algorithms, the proposed fusion algorithm can be well applied to DC-CASSI and maximum improving the spatial resolution of multispectral coded image while preserving spectral characteristics of the multispectral coded image. © 2021 SPIE.

关键词Image fusion Improved NSST PCNN DC-CASSI
作者部门光电跟踪与测量技术研究室
DOI10.1117/12.2605896
收录类别EI
ISBN号9781510646957
语种英语
ISSN号0277786X;1996756X
EI入藏号20214611146487
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/95377
专题光电跟踪与测量技术研究室
通讯作者Song, Chong
作者单位1.Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an; 710000, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China;
3.95972 troops, China
推荐引用方式
GB/T 7714
Song, Chong,Zeng, Litang,Jiang, Kai,et al. Fusion method of multispectral and panchromatic images based on NSST and improved PCNN[C]:SPIE,2021.
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
Fusion method of mul(512KB)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
[Song, Chong]的文章
[Zeng, Litang]的文章
[Jiang, Kai]的文章
百度学术
百度学术中相似的文章
[Song, Chong]的文章
[Zeng, Litang]的文章
[Jiang, Kai]的文章
必应学术
必应学术中相似的文章
[Song, Chong]的文章
[Zeng, Litang]的文章
[Jiang, Kai]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。