Color night vision through fusion of images derived from visible and thermal infrared sensors has come into application. A lot of research of perceptual or subjective evaluation of color fusion algorithms is conducted by the TNO, MIT and NRL[1-5]. Objective evaluation is becoming an increasing issue. A good fusion algorithm should preserve or enhance all of the useful features, i.e., targets pop out and content or details from the source images. Objective: The goal of our research is to predict details and target detectability of color fusion images by measuring image contrast. Methods: A color image contrast metric, which was designed to compute how much details for natural images, is employed to measure details and target detectability of color fusion images in this paper. A sub-band contrast index is defined, the first band contrast index indicates the level of details, and higher band contrast indexes indicate the level of target detectability. Results: The perceptual details have high correlation with the first sub-band contrast indexes, and the perceptual target detectability has correlation with higher sub-band contrast indexes. This means the sub-band contrast indexes may predict details and target detectability, however, noise effect on details need to be considered and prediction of target detectability need to be improved.