Image Registration Using Mutual Information with Particle Swarm Optimization

In this article, we present a complete source code implementation for image registration based on mutual information. The implementation utilizes particle swarm optimization (PSO) algorithm and can be directly executed without modifications. We provide detailed explanations of the algorithm's implementation specifics, including how mutual information is calculated for image similarity measurement and how PSO optimizes the transformation parameters. The code structure includes key functions for handling affine transformations, computing joint histograms, and implementing the PSO iteration process with velocity and position updates. We also discuss parameter tuning strategies for population size, inertia weight, and acceleration coefficients to achieve optimal registration accuracy. Comprehensive usage instructions are provided to help users easily integrate this solution into their own projects, with clear comments explaining each module's functionality and interface requirements.