基于改进Hausdorff测度和遗传算法的SAR图像与光学图像匹配

提出了一种新的基于边缘的合成孔径雷达（SAR）图像与光学图像匹配算法。在这种算法中，首先针对SAR图像低信噪比（SNR）与乘性噪声模型的固有特性提出了一种边缘特征的提取方法。在获取光学图像与SAR图像边缘图的基础上，根据Hausdorff距离具有强抗干扰能力和容错能力的特点，采用了改进的Hausdorff距离作为相似性测度。在搜索策略上，根据遗传算法的固有的并行性，采用遗传算法来加快搜索的速度。通过大量基于同一地区的光学图像与SAR图像匹配的试验结果表明，这种算法鲁棒性好，匹配精度高，计算速度快。

Matching SAR Image to Optical Image Using Modified Hausdorff Distance and Genetic Algorithms

A novel algorithm of matching synthetic aperture radar (SAR) image to Optical image based on lineal feature using Hausdorff distance combined with genetic algorithm is proposed. A new method to extract lineal feature from low SNR SAR image is presented. Based on the edge image from SAR and Optical image, modified Hausdorff distance is adopted as a similarity measure because it is insensitive to noise. In searching strategy, genetic algorithm is used to achieve high computation speed for its inertial parallel. Experimental result using real SAR and Optical images demonstrate that the algorithm is robust, fast and can achieve high matching accuracy.