Pan-Sharpening Using Weighted Red-Black Wavelet

	Pan-Sharpening Using Weighted Red-Black Wavelet
	Qingjie Liu; Yunhong Wang; Zhaoxiang Zhang; Lining Liu
	2012-11-11
会议日期	11-15 November 2012
会议地点	Tsukuba, Japan
关键词	Principal Component Analysis Correlation Remote Sensing Multiresolution Analysis Spatial Resolution Discrete Wavelet Transforms
英文摘要	In 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.
会议录	ICPR 2012
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/13263]
专题	自动化研究所_类脑智能研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Qingjie Liu,Yunhong Wang,Zhaoxiang Zhang,et al. Pan-Sharpening Using Weighted Red-Black Wavelet[C]. 见:. Tsukuba, Japan. 11-15 November 2012.