Image Registration Using MATLAB Toolbox with Feature Point Extraction

During the image registration process using MATLAB toolbox, it's essential to extract feature points from the images. These feature points serve as key landmarks to compute spatial transformations between two images, enabling their proper alignment. Feature points represent distinct locations in images with unique characteristics that can be reliably detected and utilized for registration purposes. Once these feature points are extracted, various algorithms such as RANSAC (Random Sample Consensus) or least-squares optimization can be employed to establish correspondences between them, facilitating accurate image registration. In MATLAB implementation, this typically involves using functions like detectSURFFeatures() or detectORBFeatures() for feature detection, followed by matchFeatures() for correspondence matching and estimateGeometricTransform() for transformation estimation. Therefore, feature point extraction constitutes a critical step in achieving successful image registration, forming the foundation for subsequent transformation calculations and alignment operations.