期刊论文详细信息
Remote Sensing
Unsupervised Change Detection Using Fuzzy Topology-Based Majority Voting
Ting Dong1  Pan Shao1  Zhewei Liu2  Wenzhong Shi2 
[1] College of Computer and Information Technology, China Three Gorges University, Yichang 443002, China;Department of Land Surveying and Geo-Informatics, Smart Cities Research Institute, The Hong Kong Polytechnic University, Hong Kong 999077, China;
关键词: remote sensing;    unsupervised change detection;    fuzzy topology;    majority voting;    conflict management;   
DOI  :  10.3390/rs13163171
来源: DOAJ
【 摘 要 】

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

【 授权许可】

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