基于GEPSO模型的面向对象遥感图像分类

Object-oriented Remote Sensing Image Classification Based on GEPSO Model

针对演化算法的寻优能力,提出了基于GEPSO(GEP Optimized by PSO)模型的面向对象遥感图像分类方法。先对遥感图像进行分割,选择特征集,然后利用GEPSO算法为每类图像对象构造一个类中心。构造类中心的过程先利用GEP搜索一个次优解,再根据这个次优解利用PSO搜索最优解。实验结果表明,基于GEPSO模型的面向对象遥感图像分类方法具有较高的分类精度。

According to the optimization capability of evolutionary algorithms, we proposed an object-oriented remote sensing image classification method based on GEPSO （GEP Optimized by PSO, GEPSO）model. Firstly, image segmentation was done, feature set was selected for the remote sensing image, and then uses GEPSO algorithm was used to construct a class center for each type of image objects. The process of constructing class centers firstly makes use of GEP to search a suboptimal solution, and then uses PSO to search the optimal solution with the suboptimal. Experimental results show that the object-oriented remote sensing image classification method based on GEPSO model has higher classification accuracy.