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题名:
A novel remote sensing image fusion scheme based on NSCT and Compressed Sensing
作者: Wan, Peng1; Song, Zongxi2
出版日期: 2017
会议名称: Applied Optics and Photonics China: Optical Sensing and Imaging Technology and Applications, AOPC 2017
会议日期: 2017-06-04
会议地点: Beijing, China
DOI: 10.1117/12.2285590
通讯作者: Wan, Peng
英文摘要:

In this letter, we propose a novel remote sensing image fusion method based on the non-subsampled contourlet transform and the compressed sensing (CS) theory.[2][3] Method First, the IHS transformation of the multispectral images is conducted to extract the I component. Secondly, the panchromatic image and the component intensity of the multispectral image are decomposed by NSCT. Then the NSCT coefficients of high and low frequency subbands are fused by different rules, respectively. For the high frequency subbands, the absolute maximum selection rule is used to integrate high-pass subbands; while the adaptive regional energy weighting rule is proposed to fuse low-pass subbands. The sparse coefficients are fused before being measured by Gaussian matrix. The fused image is accurately reconstructed by Compressive Sampling Matched Pursuit algorithm (CoSaMP). Some experiments are taken to investigate the performance of our proposed method, and the results prove its superiority to the counterparts. © 2017 SPIE.

收录类别: EI ; ISTP
会议录: AOPC 2017: Optical Sensing and Imaging Technology and Applications
会议录出版者: SPIE
语种: 英语
作者部门: 空间光学应用研究室
卷号: 10462
产权排序: 1
ISBN号: 9781510614055
ISSN号: 0277786X
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.opt.ac.cn/handle/181661/29919
Appears in Collections:空间光学应用研究室_会议论文

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作者单位: 1.Space Optics Laboratory, Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an, 710119, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China

Recommended Citation:
Wan, Peng,Song, Zongxi. A novel remote sensing image fusion scheme based on NSCT and Compressed Sensing[C]. 见:Applied Optics and Photonics China: Optical Sensing and Imaging Technology and Applications, AOPC 2017. Beijing, China. 2017-06-04.
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