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中文摘要：
提出了一种无监督SAR图像变化检测算法,利用数据聚类思想,通过进化算法寻找最小均方误差,得到变化检测结果.在原有Memetic算法基础上,针对图像自身特点,提出全新的搜索策略并根据当前检测结果动态调整局部搜索算法,实现了粗细结合的搜索过程.算法不受分布模型限制,不需要先验知识,适用性较强.将改进的算法与GA、ICSA及原MA进行比较,实验证明,该算法可以快速收敛.对真实SAR图像进行检测,可以得到较好的检测结果.
英文摘要：
This paper proposed an unsupervised technique for detecting changed areas between multitemporal SAR images.Different with the original ones,the clustering method was used here to find the change map by minimizing mean square error with evolution algorithm.After introducing the image character,a new search strategy in Memetic algorithm was given here,which adjusted the local search algorithm according to the current detection result.The approach was distribution free and did not need priori knowledge.The experimental results obtained on the real SAR images showed that the proposed method had a higher convergence speed than GA,ICSA and original MA,the detection results demonstrated the effectiveness of the proposed algorithm.
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