An SAR and optical image fusion algorithm coupling non-local self-similarity and divergence

doi:10.6046/zrzyyg.2021411

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Abstract

Currently, the high-quality fusion of SAR and optical images is a hot research topic. However, the significant radiation difference and weak gray correlation between SAR and optical images greatly reduce the fusion quality. In this regard, this study proposed a SAR and optical remote sensing image fusion algorithm that coupled non-local self-similarity and divergence. First, images were decomposed in the frequency domain. Then, the non-local directional entropy and divergence were used as characteristic parameters to guide the fusion of low- and high-frequency components, respectively. Finally, the fusion components were reconstructed to obtain fusion images with clear structural features and rich spectral information. The comparative experiments verified the effectiveness of the proposed algorithm in fusing SAR with optical images and its superiority in maintaining structural features and reducing spectral distortion.

Keywords SAR and optical image non-subsampled contourlet transform global feature image fusion hyper-spherical color space

ZTFLH:

TP751

Issue Date: 20 March 2023

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	Articles by authors

	Yukai FU
	Shuwen YANG
	Heng YAN
	Qing XUE
	Weili HONG
	Hang SU

Cite this article:

Yukai FU,Shuwen YANG,Heng YAN, et al. An SAR and optical image fusion algorithm coupling non-local self-similarity and divergence[J]. Remote Sensing for Natural Resources, 2023, 35(1): 99-106.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021411 OR https://www.gtzyyg.com/EN/Y2023/V35/I1/99

Fig.1 Schematic diagram of NSCT decomposition

Fig.2 Flow chart of the proposed fusion algorithm

Tab.1 Data information of the experiment

Fig.3 Fusion result of experiment 1

Fig.4 Fusion result of experiment 2

Fig.5 Fusion result of experiment 3

Tab.2 Objective evaluation indicators of 2 groups of experiments

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