Pan-Sharpening Using Weighted Red-Black Wavelet

CASIA OpenIR > 模式识别实验室

	Pan-Sharpening Using Weighted Red-Black Wavelet
	Qingjie Liu; Yunhong Wang; Zhaoxiang Zhang; Lining Liu
	2012-11-11
会议名称	International Conference on Pattern Recognition
会议录名称	ICPR 2012
会议日期	11-15 November 2012
会议地点	Tsukuba, Japan
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.
关键词	Principal Component Analysis Correlation Remote Sensing Multiresolution Analysis Spatial Resolution Discrete Wavelet Transforms
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13263
专题	模式识别实验室
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],2012.