The evaluation ofimagefusion performance is an active area of research with a variety ofdiferent approaches under investigation.Examples of techniques include those which aim to evaluate the quality offused images for human display and are based on perception metrics, and others which utilise 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 metricsfor 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 diferent fusion architectures over a range of trials and different cameras. Comparisons offused images to the source imagery are made and consideration is also given to the temporalperformance ofthe methodpresented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.