Fusion of Hyperspectral and LiDAR Data Using Sparse and Low-Rank Component Analysis.

IEEE Transactions on Geoscience and Remote Sensing(2017)

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摘要
The availability of diverse data captured over the same region makes it possible to develop multisensor data fusion techniques to further improve the discrimination ability of classifiers. In this paper, a new sparse and low-rank technique is proposed for the fusion of hyperspectral and light detection and ranging (LiDAR)-derived features. The proposed fusion technique consists of two main steps. ...
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关键词
Feature extraction,Laser radar,Hyperspectral imaging,Sensors,Data mining,Gray-scale
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