Scale-Invariant Feature Transform (SIFT) Source Code for Image Stitching Algorithms

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Resource Overview

Fully functional SIFT source code for image stitching algorithms, tested and optimized with detailed implementation notes. Particularly helpful for MATLAB beginners to understand feature detection, matching, and image composition techniques.

Detailed Documentation

This repository provides the complete source code implementation of Scale-Invariant Feature Transform (SIFT) algorithm specialized for image stitching applications. The code has been thoroughly tested and optimized to ensure full functionality. For MATLAB beginners, this implementation serves as an excellent educational resource to understand key computer vision concepts including: Gaussian pyramid construction for scale-space analysis, keypoint detection using Difference of Gaussians (DoG), orientation assignment with gradient histograms, and feature descriptor generation using 128-dimensional vectors. The code demonstrates practical image stitching workflow including feature matching using nearest neighbor search, RANSAC-based homography estimation, and image warping/blending techniques. This hands-on implementation provides solid foundation for learning and applying advanced image processing algorithms in real-world projects.

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