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Sensors 2017, 17(1), 89; doi:10.3390/s17010089

Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion

Key Laborary of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
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Academic Editor: Vittorio M. N. Passaro
Received: 11 October 2016 / Revised: 30 November 2016 / Accepted: 26 December 2016 / Published: 5 January 2017
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [27840 KB, 6 January 2017; original version 5 January 2017]   |  

Abstract

Since WorldView-2 (WV-2) images are widely used in various fields, there is a high demand for the use of high-quality pansharpened WV-2 images for different application purposes. With respect to the novelty of the WV-2 multispectral (MS) and panchromatic (PAN) bands, the performances of eight state-of-art pan-sharpening methods for WV-2 imagery including six datasets from three WV-2 scenes were assessed in this study using both quality indices and information indices, along with visual inspection. The normalized difference vegetation index, normalized difference water index, and morphological building index, which are widely used in applications related to land cover classification, the extraction of vegetation areas, buildings, and water bodies, were employed in this work to evaluate the performance of different pansharpening methods in terms of information presentation ability. The experimental results show that the Haze- and Ratio-based, adaptive Gram-Schmidt, Generalized Laplacian pyramids (GLP) methods using enhanced spectral distortion minimal model and enhanced context-based decision model methods are good choices for producing fused WV-2 images used for image interpretation and the extraction of urban buildings. The two GLP-based methods are better choices than the other methods, if the fused images will be used for applications related to vegetation and water-bodies. View Full-Text
Keywords: pansharpening; WorldView-2; quality indices; information indices pansharpening; WorldView-2; quality indices; information indices
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Li, H.; Jing, L.; Tang, Y. Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion. Sensors 2017, 17, 89.

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