The characteristics of global coupling and pulse synchronization of Pulse Coupled Neural Network (PCNN) can be used to solve the problem that the selection of high-frequency sub-band coefficients of fused images does not conform to human visual characteristics. However, PCNN has many problems in multi-source image fusion, such as complex model structure and complicated parameter setting. As to the model structure of PCNN, two kinds of methods for model optimization are analyzed, and the general law of PCNN when applied in multi-source image fusion is summarized, which provides a reference for better application of PCNN in multi-source image fusion.