MATLAB Code Implementation for Image Stitching

This implementation demonstrates image stitching methodology using MATLAB. The process begins with SIFT (Scale-Invariant Feature Transform) algorithm to extract distinctive keypoints from input images. The code utilizes feature descriptors for robust point matching between images, employing techniques like k-nearest neighbors for descriptor matching. Subsequently, we compute the homography matrix using RANSAC (Random Sample Consensus) method to handle outliers and ensure accurate transformation estimation. The calculated homography matrix enables affine transformation of images to align them properly in a common coordinate system. Finally, the transformed images are blended together using weighted averaging or seam-finding algorithms to create a seamless panoramic output. The code contains detailed inline comments explaining each computational step, parameter selection rationale, and optimization considerations for researchers and developers interested in computer vision applications.