Fusion performance using a validation approach

The evaluation of image fusion performance is an active area of research with a variety of different approaches under investigation. Examples of techniques include those which aim to evaluate the quality of fused images for human display and are based on perception metrics, and others which utilize standard image metrics to measure edge densities, noise and other such characteristics. This latter approach can produce a good performance estimate under ideal conditions but starts to break-down in high noise environments, for example. A novel solution is to use image validation metrics for the evaluation. Image validation metrics are concerned more with the differences between images than the absolute pixel values and as such should exhibit greater resilience to changing environmental conditions. This paper furthers existing work in this area to include a family of validation metrics for image fusion and draws upon existing image validation tools to expedite the process. Assessment of fusion performance is carried out between different fusion architectures over a range of trials and different cameras. Comparisons of fused images to the source imagery are made and consideration is also given to the temporal performance of the method presented.