Tone mapping is an efficient image matching algorithm adaptive to brightness and contrast variation. Due to the complex and nonconforming relation between multi-sensor images, tone mapping can hardly be directly used on multi-sensor images to achieve satisfactory results. To improve the matching rate, the local tone mapping algorithm is proposed, which includes the following steps: Firstly, the template map is divided into nonoverlapping blocks., Then, each block is processed through histogram equalization and weak slice transform. Next, the distance maps are calculated for every block by local tone mapping. Finally, the matching result is obtained by fusion all these distance maps. Experimental results show that, the matching rate of local tone mapping significantly outperforms tone mapping and mutual information, while its computation time is slightly longer than that of the tone mapping and less than that of the mutual information.