Abstract
In this paper, the [Formula: see text]-Renyi entropy and [Formula: see text]-Renyi-based mutual information (RMI) are first introduced. Then the influence of the parameter [Formula: see text] on the curve of the RMI and the computational load of image registration are discussed and analyzed to explore the appropriate parameter ranges. Finally, the RMI with the appropriate parameter [Formula: see text] is viewed as the similarity measure between the reference and floating images. In the experiments, the Simplex method is chosen as the multi-parameter optimization one. The experimental results reveal that the proposed method has low computational load, fast registration and good registration accuracy. It is adapted to both mono-modality and multi-modality image registrations.
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