The existing image fusion methods have an edge ladder effect in varying degrees, which leads to some spatial artifacts introduced into the fused image. This paper proposes a new method to solve the poor robustness in the process of image fusion, that is, forward-backward self-correcting diffusion(FBSD) guided feature reconstruction. According to the differences between features after decomposition, a hybrid fusion strategy based on expectation-maximization algorithm and principal component analysis algorithm is designed. Finally, the evaluation index is used to evaluate the performance of the proposed algorithm, and it is verified that this method is better than the existing image fusion methods in dealing with the edge step effect, and the fusion decision is effective.