MATLAB Code Implementation for Two-Image Stitching

This code implements a MATLAB-based approach for stitching two images together. The implementation begins by reading two input images that share common feature points, typically using functions like `imread()` for image input. Feature points are then extracted using algorithms such as SIFT (Scale-Invariant Feature Transform) or SURF (Speeded-Up Robust Features) through MATLAB's Computer Vision Toolbox functions like `detectSIFTFeatures()` or `detectSURFFeatures()`. Image registration is performed to ensure precise alignment between the two images, which may involve estimating a geometric transformation (such as affine or projective transformation) using matched feature points through functions like `estimateGeometricTransform()`. For the final integration phase, the code employs an averaging method where overlapping regions between the aligned images are blended by calculating pixel-wise averages. This technique effectively minimizes visible seams and enhances overall stitching quality. The complete pipeline achieves seamless image stitching and produces a coherent final composite image through these systematic processing steps.