A visible and infrared image fusion algorithm based on saliency features is proposed to improve fusion quality of objects. The saliency detector is introduced to process the infrared image for generating the saliency map. The salient interest points are extracted in the image by further analyzing the IR image and detecting interest points. The saliency areas are identified by calculating the convex hull of salient interest points, and the target positioning becomes more accuracy by using salient interest points to optimize the initial salient mapping. The background area of visible light image is obtained according to the region mapping, and the final fusion image is obtained by using different fusion rules to fuse the target and background regions. Results show that this algorithm has advantages with clearer detail texture of fusion image in standard deviation, joint entropy and edge information factor indexes compared with the common visible image fusion technique.