To optimize the architecture of weighted average multiresolution image fusion algorithm, an extended weighted average multiresolution image fusion model to control the decision map only with the match measure is presented based on the Piella pixel-level multiresolution image fusion framework. The extended model changes the fusion pattern that the decision factor must be decided by both activity measure and match measure in the conventional weighted average multiresolution image fusion model. Since the activity measure is removed in the extended model, the corresponding algorithm architecture is rather simpler. By taking the correlated signal intensity ratio as the match measure, a weighted average multiresolution image fusion method based on the extended model is proposed. The experiment on fusing infrared and visible images shows that the proposed method is able to produce better fusion results than the conventional ones and its Edge Fusion Quality Index(EFQI) and Weight Fusion Quality Index(WFQI)has increased by 2.9% and 1.8%, respectively.Moreover, it achieves much lower computational complexity for the decision factor with decreased multiplication and addition times of 66.7% and 33.3%, respectively.