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Discriminatively guided filtering (DGF) for hyperspectral image classification

  • Published:2018-01 Issue: Volume:275 Page:1981-1987
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Wang Ziyu,Hu Huafeng,Zhang Lefei,Xue Jing-Hao

Funder

EPSRC

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference39 articles.

1. Advances in hyperspectral image classification: earth monitoring with statistical learning methods;Camps-Valls;IEEE Signal Process. Mag.,2014

2. Classification of hyperspectral remote sensing images with support vector machines;Melgani;IEEE Trans. Geosci. Remote Sens.,2004

3. Three-dimensional wavelet texture feature extraction and classification for multi/hyperspectral imagery;Guo;IEEE Geosci. Remote Sens. Lett.,2014

4. A discriminative manifold learning based dimension reduction method for hyperspectral classification;Du;Int. J. Fuzzy Syst.,2012

5. Manifold-learning-based feature extraction for classification of hyperspectral data: a review of advances in manifold learning;Lunga;IEEE Signal Process. Mag.,2014
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