Unsupervised Change Detection Using Fuzzy Topology-Based Majority Voting

Remote sensing change detection (CD) plays an important role in Earth observation. In this paper, we propose a novel fusion approach for unsupervised CD of multispectral remote images, by introducing majority voting (MV) into fuzzy topological space (FTMV). The proposed FTMV consists three principal stages: (1) the results different difference images produced C-means algorithm are combined using modified MV, and initial map is obtained; (2) topology theory, automatically partitioned two parts: weakly conflicting part strongly part; (3) pixels that possess little or no conflict assigned to current class, while pixel patterns with strong conflicts often misclassified relabeled supported connectivity topology. can integrate merits largely solve problem during fusion. Experimental on real confirm effectiveness efficiency method.