A Region-Based Image Fusion Method Using the Expectation-Maximization Algorithm

We present a novel region-based image fusion method using a rigorous application of estimation theory. This method takes advantage of the similar intensity or texture in a region for fusion. A statistical image formation model using Gaussian mixture distortion is built for each region and the EM (expectation-maximization) algorithm is used in conjunction with the model to develop the region-level EM fusion algorithm to produce the fused image. Since in most applications of image fusion, objects carry the information of interest and regions can be used to represent objects, the region-based fusion approaches could be more meaningful than pixel-based methods. Our experiments demonstrate the efficiency of the proposed region-base fusion method and the advantages in dealing with region interface artifacts for concealed weapon detection and night vision applications.