부산대학교 도서관

Monitoring sea ice activities is particularly critical to safe naval operations in the Arctic Ocean. Accurately tracking sea ice motions is essential to validate or even improve sea ice models for ice hazard forecasts at a fine scale. Fine-scale motions can be tracked from high-resolution radar or optical satellite imagery but with limited coverage. Daily motions over the entire Arctic are retrievable from passive microwave data, but at a much lower spatial resolution. Thus, providing motions at the passive microwave spatial and temporal coverage, but at an enhanced spatial resolution, will be a significant benefit. To break the resolution limitation and to boost tracking accuracy, a sequential super-resolved fine-scale sea ice motion tracking framework is proposed in which a hybrid example-based single image super-resolution algorithm is employed before the tracking procedure. Experiments demonstrate that the proposed framework significantly improves the tracking performance in both accuracy and robustness for a benchmark algorithm and a recently proposed state-of-the-art tracking algorithm.