Open Turbulent Image Set (OTIS)
This provides a standardized benchmark for researchers working on turbulence mitigation in long-distance imaging, though it is incremental as it addresses a data gap rather than introducing new methods.
The authors tackled the lack of a common dataset for evaluating turbulence mitigation algorithms by creating OTIS, a new dataset with sequences acquired through turbulent atmosphere and corresponding groundtruth, which facilitates objective comparisons between algorithms.
Long distance imaging is subject to the impact of the turbulent atmosphere. This results into geometric distortions and some blur effect in the observed frames. Despite the existence of several turbulence mitigation algorithms in the literature, no common dataset exists to objectively evaluate their efficiency. In this paper, we describe a new dataset called OTIS (Open Turbulent Images Set) which contains several sequences (either static or dynamic) acquired through the turbulent atmosphere. For almost all sequences, we provide the corresponding groundtruth in order to make the comparison between algorithms easier. We also discuss possible metrics to perform such comparisons.