Theoretical analysis of an information-based quality measure for image fusion

While recently a few image fusion quality measures have been proposed, analytical studies of these measures have been lacking. Here, we focus on one popular mutual information-based quality measure and weighted averaging image fusion. Based on an image formation model, we obtain a closed-form expression for the quality measure and mathematically analyze its properties under different types of image distortion. Tests with real images are also presented which agree with the conclusions of the analytical results. The results show the quality measure studied does not generally properly characterize increases in the distortion (noise and blurring) of the images which are input into a weighted averaging fusion algorithm.