Mutual Information Entropy-Based Image Registration Method with GUI Implementation

The mutual information entropy-based image registration method is a robust technique for aligning multiple images through information-theoretic similarity measurement. This implementation includes not only the core registration algorithm but also an intuitive GUI interface, enabling beginners to easily experiment with parameter settings and visualize results. The MATLAB-based solution employs key functions such as mutualinfo() for entropy calculation and fminsearch() for optimization, implementing a multi-resolution approach to enhance registration accuracy and computational efficiency. For students new to image registration or MATLAB GUI development, this project provides hands-on experience with practical implementations of registration workflows, including feature extraction, transformation estimation, and interpolation techniques. The method achieves precise alignment of multimodal images through histogram-based joint probability distribution analysis and gradient descent optimization, making it valuable for both academic research and real-world applications like medical imaging fusion and remote sensing analysis.