Adaptive regularized scheme for remote sensing image fusion

Sizhang TANG, Chaomin SHEN, Guixu ZHANG

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Front. Earth Sci. ›› 2016, Vol. 10 ›› Issue (2) : 236-244. DOI: 10.1007/s11707-015-0514-7
RESEARCH ARTICLE

Adaptive regularized scheme for remote sensing image fusion

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Abstract

We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a “grey world” assumption to achieve visual uniformity. We propose a fusion operator that can automatically select the total variation (TV)–L1 term for edges and L2-terms for non-edges. To implement our algorithm, we use the steepest descent method to solve the corresponding Euler–Lagrange equation. Experimental results show that the proposed algorithm achieves remarkable results.

Keywords

remote sensing image fusion / adaptive regulariser / variational method / steepest descent method

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Sizhang TANG, Chaomin SHEN, Guixu ZHANG. Adaptive regularized scheme for remote sensing image fusion. Front. Earth Sci., 2016, 10(2): 236‒244 https://doi.org/10.1007/s11707-015-0514-7

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Acknowledgements

This work was supported by the National Basic Research Program of China (No. 2011CB707104) and the National Natural Science Foundation of China (Grant No. 61273298).
Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s11707-015-0514-7 and is accessible for authorized users.

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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