Investigation of a Hybrid Algorithm for Sea Ice Drift Measurements Using Synthetic Aperture Radar Images
Areal matching by phase correlation and feature tracking are two complementary methods used to measure sea ice drift between synthetic aperture radar images. This paper evaluates a new algorithm that combines the two methods. Areal matching is improved by new methods to handle large motions and rota...
Published in: | IEEE Transactions on Geoscience and Remote Sensing |
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Main Authors: | , |
Language: | unknown |
Published: |
2014
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Subjects: | |
Online Access: | https://doi.org/10.1109/TGRS.2013.2286500 https://research.chalmers.se/en/publication/195683 |
Summary: | Areal matching by phase correlation and feature tracking are two complementary methods used to measure sea ice drift between synthetic aperture radar images. This paper evaluates a new algorithm that combines the two methods. Areal matching is improved by new methods to handle large motions and rotated ice. It is shown that areal rotation can be resolved using a frequency-domain approach. Image segmentation is a prerequisite for feature tracking and achieved by a new method that performs better than Otsu's method for two-component Gaussian mixture distributions. A circular weighted median filter is found to be suitable for the filtering of the motion field. The algorithm is evaluated through a thorough analysis of the response and sensitivity to various algorithm settings. The accuracy of the algorithm varies by up to 50% for one image pair within the studied range of parameter settings, thus indicating the need for a proper initialization of the algorithm. |
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