Implementation and Evaluation of a Variety of Image Stitching Methods

Abstract: Image stitching includes image registration and image merging. Image registration can be categorized into area based, frequency based, feature based, and—a recent addition—learning-based methods. As it is not straightforward to assess stitching accuracy, a metric is adopted for measuring stitching error. Stitching success is defined by setting a threshold to this error metric. Using this definition of success,method robustness can be determined by counting the number of successes on experiments. From the four registration method categories, seven image stitchingmethods are implemented and evaluated with the parameters: overlap, noise, and rotation. Data is synthesized from larger images for the purpose of measuring robustness with respect to these parameters. Robust methods are highlighted from results and further work proposed.