DocumentCode
1439641
Title
An Optimized Approach for Pansharpening Very High Resolution Multispectral Images
Author
Zhou, Zhiqiang ; Peng, Silong ; Wang, Bo ; Hao, Zhihui ; Chen, Shaolin
Author_Institution
Inst. of Autom., Beijing, China
Volume
9
Issue
4
fYear
2012
fDate
7/1/2012 12:00:00 AM
Firstpage
735
Lastpage
739
Abstract
State-of-the-art pansharpening methods generally inject the spatial details extracted from the panchromatic (Pan) image into the multispectral (MS) images by considering different injection models. The fusion performances severely rely on the accuracy of the modeling and the estimation of model parameters. In this letter, we propose an optimized approach to avoid explicitly modeling the detail injection process. The solution employs the gradient field of the Pan image for spatial enhancement. The low-pass (LP) version of the fused bands are constrained to be the most similar to the original MS bands to preserve the spectral characteristics. We use the local correlation coefficients between the MS band and the LP version of the Pan image to adjust the two sources of information based on a simple observation, and it is further optimized by considering the overall quality index Q4. Experimental results demonstrate that the proposed method outperforms the state-of-the-art multiresolution analysis-based methods.
Keywords
correlation methods; geophysical image processing; image enhancement; image fusion; image resolution; LP version; MS band; Pan image; fused bands; injection models; injection process; local correlation coefficient; low-pass version; model parameter estimation; optimized approach; panchromatic image fusion performance; quality index Q4; spatial enhancement; spectral characteristics; state-of-the-art multiresolution analysis-based method; very high resolution multispectral image pansharpening method; Adaptation models; Distortion measurement; Image fusion; Indexes; Remote sensing; Spatial resolution; Local correlation coefficients (LCCs); Pansharpening; very high resolution (VHR) multispectral images;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2011.2180504
Filename
6145610
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