Texture-based optical flow for wind velocity estimation from water vapor data

Joel R. Barnett; Andrea Bertozzi; Luminita A. Vese; Igor Yanovsky

doi:10.1117/12.2663008

12 June 2023 Texture-based optical flow for wind velocity estimation from water vapor data

Joel R. Barnett, Andrea Bertozzi, Luminita A. Vese, Igor Yanovsky

Proceedings Volume 12543, Ocean Sensing and Monitoring XV; 125430H (2023) https://doi.org/10.1117/12.2663008
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Accurate estimation of atmospheric wind velocity plays an important role in weather forecasting, flight safety assessment and cyclone tracking. Atmospheric data captured by infrared and microwave satellite instruments provide global coverage for weather analysis. Extracting wind velocity fields from such data has traditionally been done through feature tracking, correlation/matching or optical flow means from computer vision. However, these recover either sparse velocity estimates, oversmooth details or are designed for quasi-rigid body motions which over-penalize vorticity and divergence within the often turbulent weather systems. We propose a texture based optical flow procedure tailored for water vapor data. Our method implements an L1 data term and total variation regularizer and employs a structure-texture image decomposition to identify key features which improve recoveries and help preserve the salient vorticity and divergence structures. We extend this procedure to a multi-fidelity scheme and test both flow estimation methods on simulated over-ocean mesoscale convective systems and convective and extratropical cyclone datasets, each of which have accompanying ground truth wind velocities so we can qualitatively compare performances with existing optical flow methods.

Conference Presentation

Citation Download Citation

Joel R. Barnett, Andrea Bertozzi, Luminita A. Vese, and Igor Yanovsky "Texture-based optical flow for wind velocity estimation from water vapor data", Proc. SPIE 12543, Ocean Sensing and Monitoring XV, 125430H (12 June 2023); https://doi.org/10.1117/12.2663008

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