Remote sensing image fusion in the non-subsampled shearlet transform domain

被引：0

作者：

Xiong Z. ^{[1
,2
]}

Liu M. ^{[1
,3
]}

Guo Q. ^{[2
]}

Li A. ^{[2
]}

机构：

[1] School of Electronic Engineering, Heilongjiang University, Harbin

[2] Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing

[3] Key Laboratory of Information Fusion Estimation and Detection, Harbin

来源：

Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2022年 / 43卷 / 02期

关键词：

Guided filtering; Image fusion; Multispectral image; Non-subsampled shearlet transform (NSST); Panchromatic image; Regional sharpness weighting;

D O I：

10.11990/jheu.202012011

中图分类号：

学科分类号：

摘要：

Image fusion of multispectral and panchromatic images has been widely applied to improve the effectiveness of subsequent image processing to address the need for further image application. A new image fusion method based on regional sharpness weighting and guided filtering in the non-subsampled shearlet transform (NSST) domain is proposed in this paper. First, the luminance component of the multispectral and panchromatic images is respectively decomposed into low- and high-frequency sub-bands by the NSST. Then, the fusion rules of high- and low-frequency sub-bands are respectively designed in accordance with the characteristics of high- and low-frequency sub-bands. Finally, the fusion image is obtained by taking the inverse NSST and IHS transform. Compared with six typical fusion methods through nine indicators, including spectral and spatial quality evaluation, the experimental results show that the proposed method achieves optimal performance considering the subjective visual effect and objective assessment and effectively preserves the spectral information while improving spatial resolution. Copyright ©2022 Journal of Harbin Engineering University.

引用

页码：290 / 297

页数：7

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