Image Stitching Method Implementation Using MATLAB

This article discusses the implementation of image stitching using MATLAB programming environment. The code is designed to run in MATLAB R2009a and is structured as an M-file script. The program requires four input images designated as r_image1, r_image2, r_image3, and r_image4, which are processed to generate a composite output image labeled as Image A. The implementation leverages MATLAB's comprehensive image processing toolbox, utilizing key functions for feature detection, transformation estimation, and image blending. The algorithm typically involves these sequential steps: feature point detection using methods like SIFT or SURF, feature matching between adjacent images, homography matrix calculation for spatial transformation, and final image warping with seamless blending techniques. The code incorporates error handling for mismatch resolution and quality optimization parameters to ensure accurate alignment and minimal visual artifacts in the stitched result. Additional techniques include brightness normalization and edge smoothing algorithms to maintain consistency across the final composite image. This technical walkthrough provides practical implementation insights and methodology explanations to help readers better understand and utilize the program effectively. The article aims to assist researchers and developers working on image stitching applications, enabling them to accomplish this task with improved efficiency and technical understanding.