When it comes to image fusion, the wavelet transform is the most generally used method. It combines the information included in the source photos' information in the wavelet domain according to a set of fusion rules, and it is the most widely used method. It is, however, difficult to develop a fair fusion rule because of the uncertainty in the contributions of the source images to the fused image.The capacity to include as much information as possible into the fused image becomes the most difficult problem. ThisWhen developing an image fusion algorithm in this study, the wavelet transform and fuzzy reasoning were applied to aid in the process. In this case, the corners are rounded.The source photographs are identified via the application of a set of fuzzy criteria that are applied to each image. This paper describes in detail the hardware architecture used for fuzzy-based photo fusion.is put forth as a possible solution. Using the recommended hardware design, resource usage may be reduced, making it especially well suited for low-end computer systems.applications that need a large amount of power There are just two line memory buffers in the design, and they each have a limited amount of computing capability.It minimises complexity, resulting in cheaper hardware costs, and it is suited for a broad variety of real-time applications, including gaming and medical applications. TheIt is estimated that the hardware design will use 4179 gates and will demand a total of 203.27 milliwatts of power.