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Pan-Sharpening Using Weighted Red-Black Wavelet
Qingjie Liu; Yunhong Wang; Zhaoxiang Zhang; Lining Liu
Conference NameInternational Conference on Pattern Recognition
Source PublicationICPR 2012
Conference Date11-15 November 2012
Conference PlaceTsukuba, Japan
AbstractIn this paper, we propose a new method for remote sensing image pan-sharpening which is based on weighted red-black (WRB) wavelet and adaptive principal component analysis (PCA), where the adaptive PCA is used to reduce spectral distortions and the utilization of WRB wavelet is used to extract the spatial details in PAN images. To reduce the artifacts and spectral distortions in the pan-sharpened images, which were caused by the local instabilities and dissimilarities in the PAN and MS images, a local process strategy incorporating detail enhancement is introduced. The proposed method is tested on two datasets both acquired by QuickBird and compared with the existing methods. Experimental results show that our method can provide promising fused MS images at a high spatial resolution.
KeywordPrincipal Component Analysis Correlation Remote Sensing Multiresolution Analysis Spatial Resolution Discrete Wavelet Transforms
Document Type会议论文
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
GB/T 7714
Qingjie Liu,Yunhong Wang,Zhaoxiang Zhang,et al. Pan-Sharpening Using Weighted Red-Black Wavelet[C],2012.
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