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