Image Registration Algorithm Package

A packaged collection of image registration algorithms encompassing many classical registration methods. These established algorithms include: feature point matching, mutual information, and normalized cross-correlation. In image registration, feature point matching serves as a prevalent approach that involves detecting keypoints within images and establishing correspondences with matching points in other images - typically implemented using detectors like SIFT or ORB followed by descriptor matching algorithms. Mutual information operates as a similarity metric between two images, evaluating their resemblance by calculating statistical dependencies between pixel intensity distributions through histogram-based probability computations. Normalized cross-correlation represents a correlation-based registration technique that determines optimal alignment by computing cross-correlation coefficients between images, often implemented using sliding window operations with FFT acceleration for efficiency. Beyond these classical algorithms, ongoing research continues to develop novel registration methodologies to enhance both accuracy and stability in image alignment tasks.