A novel color image fusion QoS measure for multi-sensor night vision applications

Color image fusion of visible and infra-red imagery can play an important role in multi-sensor night vision systems that are an integral part of modern warfare. Image fusion minimizes the amount of required bandwidth by transmitting the fused image rather than multiple sensor images. Color image fusion can be achieved by combining inputs from original colored sensors or by employing pseudo colorization and color transfer to grayscale images. Various quality measures have been proposed for multi-sensor grayscale image fusion techniques; but no appropriate quality measure has been devised for the quality evaluation of multi-sensor color image fusion. In this paper, we propose a novel color image fusion quality measure, Color Fusion Objective Index (CFOI) based on colorfulness, gradient similarity and mutual information techniques. Experimental results show the effectiveness of CFOI to evaluate the color and salient feature extraction introduced by color fusion techniques into the final fused imagery as well as its consistency with subjective evaluation.