Image Stitching

Image stitching is the process of combining two or more images to create a larger panoramic image. This technique is widely applied in fields such as cartography, medical imaging, and artificial intelligence. Image stitching can be achieved by moving the camera's field of view across different areas. However, variations in camera internal parameters (e.g., focal length, distortion coefficients) and external parameters (e.g., rotation, translation) may cause misalignment between images. Therefore, modern image stitching techniques typically involve identifying and correcting these discrepancies through computational methods to ensure high-quality and reliable results. Key algorithmic steps often include feature detection (using algorithms like SIFT or ORB), homography estimation, and blending techniques (such as multiband blending) to minimize visible seams. Implementation commonly utilizes OpenCV functions like cv2.Stitcher_create() or MATLAB's imageStitcher class for automated pipeline execution.