An evaluation for objectively assessing the quality of visible and infrared color fusion image is proposed. On the basis of the consideration that human perception is most sensitive to color, sharpness, and contrast when assessing the quality of color image, we propose four objective metrics: image sharpness metric (ISM), image contrast metric (ICM), color colorfulness metric (CCM), and color naturalness metric (CNM). The ISM is evaluated by image gradient information. The ICM is defined based on both gray and color histogram characteristics. A color chroma metric, as well as a color variety metric based on a color difference gradient, is proposed, respectively, to define the CCM. The CNM is defined by measuring the color distribution's similarity between the fusion image and nature image, which are of the same scene. All the color attributions are computed in the CIELAB color space. Experimental results show that the proposed objective metrics are meaningful and effective on color fusion image evaluation because they correspond well to subjective evaluation.
The image fusion system has the benefit of having simultaneous
multi-spectral data available to the user. In this paper,
we describe how to implement real-time fusion of visible and infrared image in a hardware system. In this system, we
use a CCD detector and a uncooled microbolometer focal plane arrays as the imaging detector. Image registration and
image fusion algorithm based on weighted pixel average is realized in real-time image processor. With experiment
images, analysis of reflectance and radiation characters of objects in image is given then, on the base of which we get the
spectrum distribution of some objects in fusion image. It leads to a study on a new measure of spectral information of
image. A definition of spectral information quality is given for the first time and a formula is discussed. We can get the
conclusion that: Measure on spectral information quality is significative in image fusion. The ultimate reason for increase
of information in fusion image is the increase of spectral information.