High-resolution image mosaicking plays a critical role in geomatics and remote sensing applications, allowing efficient visualization, measurement, and analysis of large-scale envi ronments. Although existing commercial tools provide standard stitching capabilities, they often lack mathematical transparency and real-time customization, limiting their utility in research and professional analysis.
This thesis introduces a systematic approach to dynamic image stitching and visualization within a C# environment. The method uses homography transformations to achieve ac curate image alignment while integrating an optimal seam-finding algorithm to improve visual coherence in overlapping regions. An exportable homography matrix supports co ordinate traceability, enabling users to perform metric evaluations on stitched images. The implementation focuses on creating a lightweight, interactive stitching prototype capable of processing two to three aerial images with high geometric fidelity and run-time efficiency.
Experimental validation confirms that the system delivers precise stitching results and sup ports visual exploration for measurement tasks. By combining mathematical clarity, dy namic responsiveness, and user adaptability, this research contributes to a modular and extensible foundation for image mosaicking in the context of geomatics, with practical rele vance for aerial inspection, photogrammetry, and spatial data visualization