基于蜂群优化模糊聚类的遥感图像变化检测

Abstract

Abstract:

In order to overcome the local optimization of the fuzzy clustering algorithm,an artificial bee colony based on fuzzy algorithm combined with the global optimization of the bee colony algorithm is proposed for change detection in remote sensing.Ratio figure and difference figure fusion method is chosen to generate the difference image (DI),and then the fuzzy clustering algorithm is adopted to recover the changed and unchanged regions of the DI by constructing two clusters,where the artificial bee colony algorithm is introduced to avoid the local minimum problems of FCM and reduce the sensitivity of the initialization values of FCM.Simulation results show the new algorithm is more robust and efficient.

Key words: fuzzy clustering;artificial bee colony algorithm;remote sensing

CLC Number:

TP301.6

JIA Cai-Jie. Change Detection in Remote Sensing Images Based on the Fuzzy Clustering Algorithm and Artificial Bee Colony Optimization[J]., 2012, 25(11): 11-.

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Change Detection in Remote Sensing Images Based on the Fuzzy Clustering Algorithm and Artificial Bee Colony Optimization

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