Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (20): 162-166.

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SAR image change detection based on multiagent genetic algorithm

XIE Wenna, QIAO Ping’an, PAN Xiaoying   

  1. School of Computer, Xi’an University of Posts & Telecommunications, Xi’an 710061, China
  • Online:2015-10-15 Published:2015-10-30



  1. 西安邮电大学 计算机学院,西安 710061

Abstract: As the conventional evolutionary algorithms are often easy to trap in local optimum value, slowly convergent and time-consuming in dealing with the problem of Synthetic Aperture Radar (SAR) images change detection. In order to solve the problems, this paper proposes an unsupervised technique, namely multiagent genetic algorithm. The processed images are used to construct the difference image by logarithmic ratio, and the difference image is processed with medium value filter. Then the method takes the gray value as input information, uses the multi-agent genetic algorithm to search the global threshold. According to the global threshold, it gets the results in change detection. Simulation results show that the proposed method is more accuracy classification, faster convergence rate and more efficient than GA, ICSA.

Key words: change detection, Synthetic Aperture Radar(SAR) image, multiagent genetic algorithm

摘要: 针对传统进化算法在SAR图像变化检测时,容易陷入局部最优,收敛速度慢,耗时过长,为了解决这些问题,提出了一种无监督的多智能体遗传SAR图像变化检测方法。利用对数比值法对预处理后的图像构造差异影像,并对差异影像进行中值滤波处理,把它的灰度值作为输入信息,通过多智能体遗传算法搜索全局阈值,根据全局阈值得到变化检测结果。仿真结果表明,该算法与GA、ICSA相比,分类准确,收敛快速,效率更高。

关键词: 变化检测, 合成孔径雷达(SAR)图像, 多智能体遗传算法