Weighted Sparse Graph Based Dimensionality Reduction for Hyperspectral Images
نویسندگان
چکیده
منابع مشابه
Hyperspectral Dimensionality Reduction by Tensor Sparse and Low-Rank Graph-Based Discriminant Analysis
Recently, sparse and low-rank graph-based discriminant analysis (SLGDA) has yielded satisfactory results in hyperspectral image (HSI) dimensionality reduction (DR), for which sparsity and low-rankness are simultaneously imposed to capture both local and global structure of hyperspectral data. However, SLGDA fails to exploit the spatial information. To address this problem, a tensor sparse and l...
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ژورنال
عنوان ژورنال: IEEE Geoscience and Remote Sensing Letters
سال: 2016
ISSN: 1545-598X,1558-0571
DOI: 10.1109/lgrs.2016.2536658