Different image types can be obtained by different sensors, but all the useful information cannot be extracted from a single image. Infrared images can capture the heat source information of scene targets in low light or severe weather conditions. Visible images provide more detail information about the scene. To obtain the rich image information, we propose a visible and infrared images fusion method based on rolling guidance filtering and saliency region extraction in this paper. A multi-scale image decomposition framework is built by using the edge preserving-smoothing algorithm. The image is decomposed into one base layer with different scales and several detail layers. Meanwhile, the saliency region extraction is implemented on each decomposition layer by combining with the rolling guidance filtering. Weight reconstruction is adopted to obtain the final fusion result. The results show that the proposed algorithm has good subjective and objective evaluation results, better fusion performance and robustness compared to other state-of-the-art fusion methods.