Mutual Information-Based Image Registration Program

The mutual information-based image registration program serves as a highly valuable tool implemented in MATLAB, facilitating deeper comprehension of mutual information principles and their practical applications. This program's architecture employs histogram-based joint probability distributions to calculate mutual information between images, typically utilizing optimization algorithms like gradient descent or Nelder-Mead simplex for parameter space exploration. Key functions include image preprocessing (intensity normalization), affine transformation modeling (rotation/translation/scaling), and mutual information maximization through iterative transformation updates. The implementation demonstrates how mutual information metrics enable precise multi-image alignment, particularly beneficial in medical imaging for structural localization and pathology identification. By integrating numerical optimization techniques with probability theory, this program significantly advances research and practical outcomes in image processing and medical image analysis domains.