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An image fusion system accepts two source images and produces a 'better' fused image. The term 'better' differs from one context to another. In some contexts, it means holding more information. In other contexts, it means getting more accurate results or readings. In general, images hold more than just the color values. Histogram distribution, dynamic range of colors, and color maps are all as valuable as the color values presenting the pictorial information of the image. This paper studies the problems of fusing images from different domains. It proposes a method to extend the fusion algorithms to fuse image properties that define the interpretation of captured images as well.