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Journal of Applied Remote Sensing

Gradient transferred pansharpening method based on cosparse analysis model
Author(s): Chang Han; Nong Sang; Hongyan Zhang; Liangpei Zhang
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Paper Abstract

The remote sensing image pansharpening problem under cosparse analysis framework is addressed. To preserve the spatial information of the high-resolution (HR) panchromatic (PAN) image, a gradient transfer strategy is proposed by introducing a gradient consistency constraint to the cosparse analysis-based remote sensing image pansharpening model. Thus, by learning the image gradient information from the HR PAN image, the spatial details of the fused image can be effectively enhanced. In the proposed method, to save running time, the cosparse analysis operator is trained offline in advance with a set of training samples. Both simulated and full-scale, real-data experiments were conducted, and the experimental results confirm that the proposed method outperforms the state-of-the-art remote sensing image fusion methods, in terms of both the visual evaluation and quantitative measurements.

Paper Details

Date Published: 11 May 2017
PDF: 18 pages
J. Appl. Rem. Sens. 11(2) 025009 doi: 10.1117/1.JRS.11.025009
Published in: Journal of Applied Remote Sensing Volume 11, Issue 2
Show Author Affiliations
Chang Han, Huazhong Univ. of Science and Technology (China)
Wuhan Business Univ. (China)
Wuhan Univ. (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)
Hongyan Zhang, Wuhan Univ. (China)
Liangpei Zhang, Wuhan Univ. (China)


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