In order to solve the problems of information loss and artifact in the fusion of visible light and infrared image, the image fusion algorithm of VI and IR based on saliency detection coupled weight mapping is proposed. The VI and IR images were decomposed into two scales to obtain the base layer and detail layer. In order to improve the fusion effect of VI and IR, a salient feature detection method was defined, and the mean filter was applied to each source image to reduce the intensity change between the pixel and its adjacent pixels for finishing the smoothing process. Then the median filter was applied to each source image to eliminate noise or artifacts for preserving the edges. By taking the difference between the mean value and the median filter output to calculate the significance characteristics, the salient information such as edges and lines is highlighted. Then, the significance detection results are normalized to construct the weight mapping for assigning the appropriate weight to the detail layer. And the basic layer and detail layer are fused by different rules, in which the weight map and detail layer are combined to get the final detail information, and the basic layer is fused by the average fusion rules. Finally, the linear combination of the final base layer and detail layer were used to construct the new image. Experimental results show that compared with the current multiscale image fusion technology, the proposed algorithm only uses twoscale decomposition, which significantly improves the fusion efficiency, and the fusion image has better fusion quality, which effectively eliminates the artifacts and less information loss in the fusion process.