Fusion of multiple images with robust random field models

A fusion of multiple sensors with different resolution and noise characteristics is considered. The fusion of two sensors is formulated as a robust estimation problem, then the two-sensor fusion algorithm is generalized to the fusion of multiple sensors. In the two-sensor fusion problem, two sensors are assumed having complimentary characteristics, one with poor resolution and the other with poor noise characteristics. The fusion of multiple sensors is done by applying the weighted sum of images obtained by pairwise fusion. The multisensor fusion algorithm is tested with simulated images and real synthetic aperture radar images. In the experiment, the fusion algorithm yielded images where both resolution and signal-to-noise ratio are substantially improved compared to images before applying the fusion.