Fast image fusion with a Markov random field

The author demonstrates that the relatively quick fusion of edge information across a number of registered images (possibly from different sensors) is possible using a Markov random field approach. The speed of the method relies on the fixing the pixel value and only optimising the boundary parameter in the model. This more simple optimisation can be undertaken with the demonstrably less computationally expensive method of iterative conditional modes (ICM). The disadvantage of using the ICM method is that it seeks the nearest local optima. However, for the experiments described here, which used real data, this was not found to be a limitation.