To address the problem of artifacts and information residuals in the existing multi-focus image fusion algorithms, an algorithm is proposed to maximize the retention of information and clarity of each region based on the focusing characteristics of the image. Firstly, the focus region decision map is obtained by region detection, which is then used for initial fusion and boundary extraction to obtain the boundary region decision map; secondly, the ACS Network is used to learn the fusion rules of multi-focus images and generate the network fusion image; finally, the initial fusion image and the network fusion image are weighted and summed according to the boundary region decision map to obtain the final fusion image. The experimental results demonstrate that the algorithm outperforms other comparable algorithms in both the focus region and the boundary region, and the evaluation indexes are improved by more than 4.8% and 1.5%, respectively; Meanwhile, the subjective effect is more in line with HVS. The experiments have proved that the algorithm achieves good results in retaining the detailed information of the source image and avoiding visual artifacts in various regions.