中文摘要：

提出广义高斯模型假设下KI双阈值法的SAR图像变化检测算法。描述了SAR差异图像上未发生变化类、后向散射减弱类和后向散射增强类的概率密度分布。基于KI准则,构建了双阈值准则函数。提出仅利用差异图像灰度直方图的最优双阈值自动选取方法,实现了3种变化与非变化类型的非监督变化检测信息提取。选取两个时相的Radarsat卫星SAR图像进行变化检测试验,结果表明该方法可行、有效。

英文摘要：

The unsupervised change detection technique on multi-temporal SAR images not only needs to detect the changed region but also subdivide the changed region in a complex geographical environment so that the backscatter enhanced class and the backscatter weakened class can be further identified.The generalized Gaussian distribution model can approximate a large variety of statistical distributions at the cost of only one additional parameter to be estimated（i.e.,the shape parameter） compared with the traditional Gaussian distribution model.In particular,the generalized Gaussian distribution model is proved to be more suitable to describe the distributions of unchanged and changed classes on SAR log-ration difference image than the Gaussian one.An change detection algorithm in SAR images based on the generalized Gaussian distribution model and KI dual thresholds criterion is proposed.The probability density distributions of the unchanged class,the backscatter enhanced class and the backscatter weakened class on SAR difference image are modeled.The dual thresholds criterion function is defined based on KI criterion.An optimal automatic dual thresholds selection approach is proposed only using the gray histogram of the difference image.The unchanged,the backscatter enhanced and the backscatter weakened classes are detected.The two temporal SAR images from Radarsat satellite are used to experiment and the results show that the proposed approach is feasible and effective.Improving the accuracy and speed of SAR image unsupervised change detection technique by using the spatial context information will be studied as a future development of this work.