A variational fusion method for remote sensing images of China’s domestic high-resolution satellites

doi:10.6046/gtzyyg.2018.02.14

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Abstract

The current panchromatic (PAN) / multispectral (MS) fusion methods do not comprehensively consider the characteristics of the remote sensing images from China’s domestic high-resolution satellites. Therefore, this paper proposes a variational fusion method for China’s domestic high-resolution images. On the one hand, the three-dimensional spectral high-fidelity model based on the spectral gradient is proposed by comprehensive consideration of the relations between the spectral bands. On the other hand, according to the existing blurring characteristics of the PAN image acquired by China’s domestic high-resolution satellites, the spatial enhancement model in consideration of the blurring degradation is developed. Finally, the fusion energy function is constructed by combining the prior knowledge of the remote sensing images, and it is solved by the classical gradient decent methods to obtain the fused image. The proposed method was tested and verified by the Gaofen-1 (GF-1) and Gaofen-2 (GF-2) satellite datasets. In addition, the popular GS, PRACS, and ATWT-M3 methods were applied for comparison from both qualitative and quantitative aspects. The experimental results show that the proposed variational high-fidelity PAN/MS fusion method comprehensively considers the characteristics of China’s domestic satellites, and hence it can maximally preserve the spectral information while effectively improve the spatial resolution of the MS images, thus achieving the best fused results.

Keywords fusion multispectral image panchromatic image variational model remote sensing

TP751.1

Corresponding Authors: Xiangchao MENG E-mail: 89642740@qq.com;mengxc@whu.edu.cn

Issue Date: 30 May 2018

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	Feng YIN
	Xiangchao MENG
	Peng LIANG

Cite this article:

Feng YIN,Xiangchao MENG,Peng LIANG. A variational fusion method for remote sensing images of China’s domestic high-resolution satellites[J]. Remote Sensing for Land & Resources, 2018, 30(2): 100-106.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.02.14 OR https://www.gtzyyg.com/EN/Y2018/V30/I2/100

Fig.1 Fusion results of the GF-1 simulated experiment

Fig.2 Fusion results of the GF-2 simulated experiment

Tab.1 Quantitative evaluation of the fusion results in the GF-1 simulated experiment

Tab.2 Quantitative evaluation of the fusion results in the GF-2 simulated experiment

Fig.3 Fusion results of the GF-1 real experiment

Fig.4 Fusion results of the GF-2 real experiment

Tab.3 Quantitative evaluation of the fusion results in the GF-1 real experiment

Tab.4 Quantitative evaluation of the fusion results in the GF-2 real experiment

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