AN ADVANCED BENCHMARKING FOR IMAGE COMPOSITING EVALUATION
This paper introduces a novel benchmarking tool for measuring the robustness of existing mosaicing algorithms in presence of a given set of disturbances. The process combines a set of partially overlapping images into a wide-view result used to represent UAV image series and orthophotography. Geometrical misalignements caused by perspective error may lead to some unpredictable artifacts and phantom effects in the mosaics. A very few solutions measure their immunity to known distortions and mainly focus on registration accuracy measurement. Only limited attention was given to characterize the response of the actual image fusion algorithms and their capacity to properly preserve content geometries. In this paper, we also introduce a new fidelity metric assessing the mosaicing response to a disturbance of a given extent used as prior information. The metric helps to better define the use cases fulfilling aerial imaging requirements.