MATLAB Implementation for Image Stitching: Cylindrical Panoramic Stitching Algorithm

This algorithm is designed for image stitching and cylindrical panoramic stitching of image sequences. It is implemented as a simulation program in MATLAB, utilizing key computer vision techniques including feature detection using SIFT or SURF algorithms, cylindrical coordinate transformation to warp images onto a cylindrical surface, and image blending methods to create seamless transitions between stitched images. The implementation typically involves these core steps: 1. Image preprocessing and cylindrical projection to reduce perspective distortions 2. Feature point detection and matching between adjacent images 3. Homography estimation to calculate optimal transformation matrices 4. Image warping and alignment using calculated transformations 5. Multi-band blending or linear blending to smooth seam lines Through this algorithm, multiple images can be seamlessly stitched into a cylindrical panoramic image. The stitching algorithm finds applications in various fields such as virtual reality environments, panoramic photography, and digital map creation. The MATLAB implementation provides a flexible framework that allows for parameter adjustment and algorithm customization based on specific project requirements.