测绘通报 ›› 2019, Vol. 0 ›› Issue (10): 105-108,118.doi: 10.13474/j.cnki.11-2246.2019.0328

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Building change detection by multi-feature fusion from high resolution remote sensing images

LI Junsheng, DANG Jianwu, WANG Yangping   

  1. School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2019-01-28 Revised:2019-04-04 Online:2019-10-25 Published:2019-10-26

Abstract: In order to make full of spectral, spatial and texture feature, a method of change detection based on fuzzy set theory and DS evidence theory is proposed. In the first step of the proposed approach,image segmentation is used to get image objects.The spectral, texture and morphological building index features of each object are extracted. Change vector analysis is adopted to calculate the difference of the corresponding features between two periods. Then, Sigmoid function is applied as membership function to get the objects membership belonging to the changing and non-changing classes respectively and to construct the basic probability assignment function(BPAF) of evidence theory.At last, evidence theory is used to fuse multi-feature information and the changed image region of building is determined via certain rules. The experimental results show that the method can fully integrate spectral, texture and morphological building index(MBI) features and improve the accuracy of building change detection.

Key words: remote sensing, multi-feature fusion, evidence theory, fuzzy set, change detection

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