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http://dx.doi.org/10.3837/tiis.2019.01.019

An Adaptive Weighted Regression and Guided Filter Hybrid Method for Hyperspectral Pansharpening  

Dong, Wenqian (State Key Lab. of Integrated Service Networks, Xidian University)
Xiao, Song (State Key Lab. of Integrated Service Networks, Xidian University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.1, 2019 , pp. 327-346 More about this Journal
Abstract
The goal of hyperspectral pansharpening is to combine a hyperspectral image (HSI) with a panchromatic image (PANI) derived from the same scene to obtain a single fused image. In this paper, a new hyperspectral pansharpening approach using adaptive weighted regression and guided filter is proposed. First, the intensity information (INT) of the HSI is obtained by the adaptive weighted regression algorithm. Especially, the optimization formula is solved to obtain the closed solution to reduce the calculation amount. Then, the proposed method proposes a new way to obtain the sufficient spatial information from the PANI and INT by guided filtering. Finally, the fused HSI is obtained by adding the extracted spatial information to the interpolated HSI. Experimental results demonstrate that the proposed approach achieves better property in preserving the spectral information as well as enhancing the spatial detail compared with other excellent approaches in visual interpretation and objective fusion metrics.
Keywords
Hyperspectral image (HSI); panchromatic image (PANI); guided filter; adaptive weighted regression; hyperspectral pansharpening;
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Times Cited By KSCI : 1  (Citation Analysis)
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