Hyperspectral Image Classification Using Metric Learning in One-Dimensional Embedding Framework

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(2017)

引用 9|浏览52
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摘要
Hyperspectral image (HSI) classification has become an active research area in the remote sensing field. In order to construct a simple and reliable classifier, learning an adequate distance metric from a given HSI dataset is still a critical and challenging task in many HSI applications. In this paper, a novel distance metric learning (DML) framework based on 1-D manifold embedding (1DME), named ...
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关键词
Kernel,Feature extraction,Hyperspectral imaging,Sorting,Euclidean distance
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