In order to solve the problems of thermal target information loss, edge structure blur and detail loss in infrared and visible image fusion, an infrared and visible image fusion algorithm is proposed based on structure-texture decomposition. Firstly, the source images are decomposed into detail layer and structural layer by structure-texture decomposition, and the detail layer is fused and enhanced by fusion rule based on structural similarity and L₂ norm. Then, a structure-average method is proposed to decompose the structural layer into luminance layer and basic layer. The absolute-value-maximum is used to fuse the luminance layer, and a fusion rule based on multi- indicators is designed for the basic layer. Finally, the fused sub-images are reconstructed to get the final fused image. In order to verify the effectiveness of our algorithm, it is compared with nine infrared and visible image fusion algorithms, and seven objective evaluating indicators are used including spatial frequency, average gradient, edge intensity, variance, visual information fidelity, the metric based on human visual perception and information entropy. The first five indicators are improved by 27.4%,36.5%,38.2%,8.5% and 23.5%, respectively. The experimental results show that the proposed algorithm not only effectively retains the infrared thermal target, but also retains the edge structure and texture details, and achieves better results in the objective evaluating indicators.