Cylindrical Panorama Stitching for Image Sequences with Supporting Algorithm Implementation

This resource presents a cylindrical panorama stitching algorithm for processing sequential images, accompanied by a MATLAB simulation program. The cylindrical panorama stitching algorithm is designed to merge multiple sequential images into a seamless cylindrical panoramic image. The implementation involves several key computational steps: first, extracting distinctive features (such as SIFT or SURF features) from each image; second, performing feature matching between adjacent images to establish correspondence points; third, calculating cylindrical projection parameters and conducting image registration to align the images geometrically; and finally, applying blending techniques (like linear or multi-band blending) to eliminate seams and create a unified panorama. The attached MATLAB simulation program provides a practical demonstration of the complete algorithm workflow. The code includes functions for cylindrical coordinate transformation, feature detection/matching using MATLAB's Computer Vision Toolbox, homography estimation, and image blending operations. Users can examine the step-by-step implementation details, modify parameters for experimentation, and test the algorithm with their own image sequences. This resource serves as both an educational tool for understanding panoramic stitching principles and a practical foundation for developing custom image stitching applications. Technical implementation highlights include: - Cylindrical projection to warp images onto a cylindrical surface - Feature detection and matching algorithms for establishing image correspondences - RANSAC-based homography estimation for robust image alignment - Alpha blending and feathering techniques for seamless image fusion We hope this comprehensive package proves valuable for your image processing projects and algorithm development endeavors.