Multi-sensor images matching is one of the key steps in vision navigation and multi-sensor images fusion. A common image matching method is to match the features detected in both images separately. However, for the images with great difference in imaging apparatuses, for example, synthetic aperture radar(SAR) image and optical image, it is hard to obtain corresponding features. A edge support (ES) algorithm is proposed to matching multi-sensor images. ES algorithm only needs to detect edge feature in one image and find the maximal support in the transform space of the other image. The ES is calculated by normalizing the summation of orientation gradient. The matching result can be obtained by optimizing the support function through genetic algorithm′s global optimum solution. Experimental results show that the ES algorithm can matching SAR image and optical image effectively.