基于变电站多模图像的自动集成配准方法

针对采集的变电站多模图像,提出了一种改进的多模态图像的自动集成配准方法。变电站多模图像的尺寸不同,所以先对其进行小波变换,以变换后得到的两幅概貌图像为待配准图像,以六种配准方法中的每一种作为一个适应度函数。使用遗传算法进行搜索,分别寻找两幅概貌图像的最佳配准位置,再映射回小波变换前的多模图像,最后使用动态可信度进行集成。实验结果证明,该方法能实现不同尺寸的多模态图像的自动配准,速度较快,鲁棒性强,比单一的配准方法准确性高,并且可以不断地修正可信度,具有较强的适应性。

Automatic synthetic registration method based on substation multi-modal images

An improved automatic synthetic registration method for substation multi-modal images is proposed.Two multi-modal images were different sizes,so wavelet transform was done.And the results were prepared for registration.In order to search the best registration position of two multi-modal images,genetic algorithm was used in the method.And one of the six methods was the fitness function of genetic algorithm in each search.Then six results were obtained for original images,and were integrated based on dynamic credibility.It is proved that automatic registration for multi-modal images of different sizes can be realized.This method is high speed and robustness,and it is more accurate than any single registration method.Besides,the credibility can be corrected dynamically.It has strong adaptability.