MATLAB Image Stitching Implementation with Homography Transformation

This MATLAB implementation provides a comprehensive image stitching solution that employs homography transformations to seamlessly merge multiple images into a panoramic view. The program utilizes computer vision techniques including SIFT or SURF feature detection to identify keypoints across images. Through RANSAC-based homography estimation, it calculates the optimal projective transformation matrix that aligns corresponding features between image pairs. The core algorithm involves four main stages: feature extraction using detectSURFFeatures() function, descriptor matching with matchFeatures(), homography matrix calculation via estimateGeometricTransform(), and final image warping employing imwarp() with projective transformations. The blending process uses weighted averaging or multi-band blending techniques to create smooth transitions between overlapping regions. This implementation allows effective stitching of images captured from varying perspectives, handling rotational and scale differences through the homography model. The code includes automatic image alignment, perspective correction, and intelligent blending to produce visually coherent composite images suitable for panoramic photography and computer vision applications.