16Hierarchical Spatial Features Learning for Image Classification
16.1Introduction
Very high resolution (VHR) remotely sensed (RS) images are widely available because of the fast development of advanced remote sensing technology. As the VHR RS images contain abundant ground information at pixel-level, they have therefore attracted end users’ attention to their application in urban mapping, precision agriculture, forest monitoring, and so on. However, the traditional RS image classification methods depending only on spectral information have been demonstrated to be inadequate (Dell’Acqua et al. 2004). On the one hand, the VHR RS image classification suffers from uncertainty of spectral information due to the low intra-class variance and ...
