Deep Learning Based Feature Selection for Remote Sensing Scene Classification

With the popular use of high-resolution satellite images, more and more research efforts have been placed on remote sensing scene classification/recognition. In scene classification, effective feature selection can significantly boost the final performance. In this letter, a novel deep-learning-based feature-selection method is proposed, which formulates the feature-selection problem as a feature reconstruction problem. Note that the popular deep-learning technique, i.e., the deep belief network (DBN), achieves feature abstraction by minimizing the reconstruction error over the whole feature set, and features with smaller reconstruction errors would hold more feature intrinsics for image representation.…

• NN
  National Natural Science Foundation of China

  Awards: 61301277, 41371431
• WU
  Wuhan University
• NK
  National Key Research and Development Program of China

  Awards: 2012CB725303, 2012CB719906