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Image fusion is the process of combining images taken from different sources, to obtain better situational awareness. In fusing source images, the objective is to combine the most relevant information from source images into a composite image. There are many Image Fusion techniques based on signal, pixel, feature and symbol level fusion. Genetic Algorithms (GA's) are used for solving optimization problems. GA can be employed to image fusion where some kind of parameter optimization is required. In this paper, an existing and three novel image fusion algorithms which use GA's are presented. The experimental results have shown that GA based image fusion algorithms outperform the existing image fusion algorithms. GA based image fusion methods are time consuming, so they cannot be adopted in real time applications, however they can be very helpful in static image fusion applications (e.g. concealed weapon detection, medical imaging, remote sensing, weather forecasting etc).