The quality of fused images mostly depends on the number of source images available. On the other hand, the optimal fusion of large numbers of images still remains as a nontrivial process. This paper presents a fuzzy logic based method which is able to mitigate such a difficulty. In our approach, we first aligned the spatial resolutions of inputs to the desired value and satisfied the histogram matching requirements. Then we fused images from multiple sensors as a weighted sum of the inputs where the weights were calculated using an entropy and intensity guided fuzzy inference system. Experimental results showed that the proposed method had enhanced image qualities over the original inputs both from the spatial and spectral perspectives.