Adaptive region-based image fusion using energy evaluation model for fusion decision

A new adaptive region-based image fusion approach is proposed. To implement image segmentation, the piecewise smooth Mumford-Shah segmentation algorithm is studied and a fast and simple method is proposed to solve the energy function. Two complementary functions u + and u - of the algorithm, which are respectively looked as objects and background of the image, are extended into the whole image domain, and they are computed by linear or nonlinear diffusion. The key to the algorithm is to make optimal fusion decisions for every segmented region. For this purpose, an evaluation approach has to be given to measure the performances of the available fusion rules. Therefore an energy-based evaluation model, derived from the Total Variation principle, is proposed. By numerical experiment it has been demonstrated that despite an increase in complexity, the new approach has shown a number of advantages over previous ones, for example the ability to preserve all relevant information and remove some of side effects such as reducing contrast and sensitive to error of registration. © 2007 Springer-Verlag London Limited.