Multi-Image Stitching Using SIFT Algorithm

This code implements image stitching for multiple overlapping images using the Scale-Invariant Feature Transform (SIFT) algorithm for feature detection and matching. The implementation includes several key stages: SIFT feature point detection using difference-of-Gaussian pyramids, keypoint localization with sub-pixel accuracy, orientation assignment for rotation invariance, and feature descriptor generation. The code then performs feature matching using nearest-neighbor search with Lowe's ratio test to eliminate ambiguous matches. A homography matrix is computed using RANSAC for robust transformation estimation between image pairs, followed by image warping and blending techniques to create seamless panoramas. The package includes original sample images and demonstrates reliable performance with excellent stitching results. The algorithm maintains high accuracy and stability even when processing large numbers of images, making it suitable for panoramic photography and computer vision applications.