CCSSM: A Toolkit for Information Extraction from Remotely Sensed Imagery

نویسندگان

  • Yong Ge
  • Chi Zhang
  • Hexiang Bai
چکیده

This paper presents a method named CCSSM (Classification of Combining Spectral information and Spatial information upon Multiple-point statistics) which is the derivation of two probability fields from the supervised classification for the spectral extraction and multiple-point simulation (MPS) for the spatial information, which then are fused. The performance of CCSSM for two-class classification has been discussed in our previous research works. This paper mainly introduces the software toolkit of CCSSM. A multiple-class classification using CCSSM is then given. * Corresponding author. [email protected].

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تاریخ انتشار 2010