MATLAB Implementation of Contour-Based Maximum Mutual Information Image Registration Algorithm

This is a contour-based maximum mutual information image registration algorithm implemented in MATLAB. The primary objective of this algorithm is to achieve image registration by comparing contour information between images. By calculating the maximum mutual information between images, the algorithm identifies optimal registration parameters. MATLAB implementation allows flexible adjustment of algorithmic details and parameters through functions like imregister and custom mutual information calculation routines.

The algorithm workflow typically involves: contour extraction using edge detection methods (e.g., Canny or Sobel operators), mutual information calculation between contour features, and optimization using techniques like gradient descent or simplex method to maximize mutual information. Key MATLAB functions employed may include edge for contour detection, mutualinfo for information theory calculations, and optimization toolbox functions for parameter search.

This algorithm finds extensive applications in medical image processing for aligning CT/MRI scans, computer vision tasks requiring precise image alignment, and remote sensing image registration. The MATLAB implementation provides researchers with customizable parameters for different imaging modalities and registration precision requirements.