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A Novel Methodology for High Resolution Sea Ice Motion Estimation

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Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges (ICPR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13645))

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Abstract

As changes in climate lead to rapid changes in Arctic sea ice dynamics, there is a pressing need to provide methods for reliably monitoring sea ice motion. High-resolution sea ice motion estimation from satellite imagery is a task still widely considered unresolved. While various algorithms exist, they are limited in their ability to provide dense and accurate motion estimates with required spatial coverage. This paper presents a novel, hybrid method using a combined feature tracking and Optical Flow approach. It outperforms existing methods in sea ice literature in both density, providing a drift field with a resolution equal to that of the image, and accuracy, with a displacement error of 74 m.

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Acknowledgements

The authors would like to thank Dr. Jennifer Hutchings, Dr. Chris Polashenski, Dr. Andy Mahoney and the other members of the SIDEx team for their contributions to this work in the form of data collection and invaluable input and feedback. This work was supported by the Office of Naval Research (ONR), Arctic and Global Prediction Program as part of the Sea Ice Dynamics Experiment (SIDEx) under award number N00014-19-1-2606.

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Authors and Affiliations

  1. Video/Image Modeling and Synthesis (VIMS) Lab, Department of Computer and Information Sciences, University of Delaware, Newark, 19716, DE, USA

    Kelsey Kaplan & Chandra Kambhamettu

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  1. Kelsey Kaplan
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  2. Chandra Kambhamettu
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Correspondence to Kelsey Kaplan .

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Editors and Affiliations

  1. York University, Toronto, ON, Canada

    Jean-Jacques Rousseau

  2. University of Ontario Institute of Technology, Oshawa, ON, Canada

    Bill Kapralos

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Kaplan, K., Kambhamettu, C. (2023). A Novel Methodology for High Resolution Sea Ice Motion Estimation. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13645. Springer, Cham. https://doi.org/10.1007/978-3-031-37731-0_24

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  • DOI: https://doi.org/10.1007/978-3-031-37731-0_24

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