A MULTI-LEVEL SYNERGISTIC IMAGE DECOMPOSITION ALGORITHM FOR REMOTE SENSING IMAGE FUSION

被引:3
|
作者
Zou, Xinshan [1 ]
Feng, Wei [1 ,2 ]
Quan, Yinghui [1 ,2 ]
Li, Qiang [3 ]
Dauphin, Gabriel [4 ]
Xing, Mengdao [5 ]
机构
[1] Xidian Univ, Sch Elect Engn, Dept Remote Sensing Sci & Technol, Xian 710071, Peoples R China
[2] Xidian Univ, Res Inst Adv Remote Sensing Technol, Xian 710071, Peoples R China
[3] Northwestern Polytech Univ, Sch Phys Sci & Technol, Xian 710072, Peoples R China
[4] Univ Paris 13, Inst Galilee, L2TI, Lab Informat Proc & Transmiss, Villetaneuse, France
[5] Xidian Univ, Acad Adv Interdisciplinary Res, Xian 710071, Peoples R China
来源
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金
中国国家自然科学基金;
关键词
image fusion; multi-level image decomposition; remote sensing; SAR image; Multispectral image;
D O I
10.1109/IGARSS46834.2022.9884942
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Image fusion is a technique for improving the image quality, and image decomposition is one of a common method of image processing. In this paper, a novel multi-level synergistic image decomposition algorithm is proposed for the fusion of remote sensing images. The fusion framework decomposes different input images at different level to extract the salient and low-rank parts, respectively. The salient parts are fused using a designed weighted fusion method based on nuclear-norm, and the low-rank parts are fused using weighted average strategy. The proposed method shows a superior fusion performance in the compared experiments with PCA and GS methods.
引用
收藏
页码:3754 / 3757
页数:4
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