Locally Linear Embedding based Example Learning for Pan-sharpening

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	Locally Linear Embedding based Example Learning for Pan-sharpening
	Qingjie Liu; Lining Liu; Yunhong Wang; Zhaoxiang Zhang
	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, a novel example based method is proposed to solve the remote sensing pan-sharpening problem, utilizing an implicit non-parametric learning framework. The high resolution (HR) and down-sampled panchromatic (PAN) images are used to train the high/low resolution patch pair dictionaries. Based on the perspective of locally linear embedding (LLE), every patch in each multi-spectral (MS) image band is modeled by its K nearest neighbors in patch set generated from low resolution (LR) PAN image, and this model can be generalized to the HR condition. The intended HR MS patch is reconstructed from the corresponding neighbors in HR PAN patches. Finally, the HR MS images are recovered by stitching these patches together. Two datasets of images acquired by Quick-Bird satellite are used to test the performance of the proposed method. Experimental results show that the proposed method performs well in preserving spectral information as well as spatial details.
关键词	Spatial Resolution Image Reconstruction Principal Component Analysis Training Remote Sensing Vectors
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/13264
专题	智能感知与计算研究中心
通讯作者	Zhaoxiang Zhang
推荐引用方式 GB/T 7714	Qingjie Liu,Lining Liu,Yunhong Wang,et al. Locally Linear Embedding based Example Learning for Pan-sharpening[C],2012.