Image Stitching Source Code with Column-Based Feature Matching

This is a source code implementation for image stitching applications. The algorithm operates through three key stages: first, it employs column-based feature matching to precisely detect overlapping areas between images by analyzing vertical pixel patterns and edge distributions. Second, grayscale consistency is maintained using histogram matching, which aligns the intensity distributions of adjacent images through statistical transformation functions. Finally, seamless blending is achieved using a weighted smoothing algorithm that applies linear gradient weights across the overlap region to eliminate visible seams. Additional enhancements can include edge sharpening algorithms to improve image clarity through convolution-based filters like unsharp masking, along with experimental integration of multiple matching algorithms such as SIFT or SURF feature detectors to boost alignment accuracy. These refinements collectively produce superior stitching results with smoother transitions and more natural-looking composite images.