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...

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Bibliographic Details
Published in:IEEE Transactions on Geoscience and Remote Sensing
Main Authors: Berg, Anders, Eriksson, Leif
Language:unknown
Published: 2014
Subjects:
Agricultural Science
Earth and Related Environmental Sciences
Oceanography
Hydrology
Water Resources
Signal Processing
Computer Vision and Robotics (Autonomous Systems)
feature tracking
sea ice motion
segmentation
SAR
C-band
rotation
phase correlation
synthetic aperture radar
Sea ice
Online Access:https://doi.org/10.1109/TGRS.2013.2286500
https://research.chalmers.se/en/publication/195683
Description
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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