A New Hyperspectral Image Identification Method Based on LSDA and OSELM
Chengjiang Zhou,
Mingli Yang,
Sasa Duan
et al.
Abstract:To solve the problems of information loss and nonlinear transformation of hyperspectral image dimensionality reduction methods and the problem that recognition methods are sensitive to noise and cannot be trained online, a new hyperspectral image identification method based on locality sensitive discriminant analysis (LSDA) and online sequential extreme learning machine (OSELM) is proposed. Firstly, LSDA is used to reduce the redundant information and data noise, and the local structure and discriminant inform… Show more
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