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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,Lining Liu,Yunhong Wang,et al. Locally Linear Embedding based Example Learning for Pan-sharpening[C],2012.
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