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School/Department:遥感信息工程学院

沈鹏

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Gender:Male

Alma Mater:中南大学

Paper Publications

A Novel Object-Oriented Rotated Intensity Matching Method for Iceberg Drift Monitoring with SAR Images
Date of Publication:2024-06-24 Hits:

DOI number:10.1109/LGRS.2024.3418834
Journal:IEEE Geoscience and Remote Sensing
Key Words:Iceberg drift, Synthetic Aperture Radar (SAR), normalized cross-correlation (NCC)
Abstract:Iceberg information in polar regions is crucial for various applications. Synthetic Aperture Radar (SAR) satellites provide high-resolution remote sensing images without being affected by weather conditions, which are widely-used for iceberg monitoring. Most current studies track icebergs by shape similarity, and use the distance between the centroids of the icebergs as the offset between the two temporal images. However, it is difficult to characterize icebergs comprehensively with a single shape similarity, the matching performance of the traditional shape similarity-based iceberg tracking method depends on the profile extraction accuracy in the iceberg detection. Furthermore, the limited coverage of satellite remote sensing images prevents the full capture of all icebergs. The drift of these icebergs in the time-series image exhibits shape variations, leading to a mismatch in the centroids, affecting the accuracy of drift velocity calculations. To address these issues, this letter proposes an object-oriented rotated intensity matching (OORIM)-based iceberg drift method that considers both the boundary shape and the intensity similarity of iceberg objects and obtains both offset information and rotation angle simultaneously. We successfully track 21 icebergs from Sentinel-1 SAR images near the Weddell Sea, and the results demonstrate the superiority of this method compared with other methods in terms of the accuracy of iceberg tracking. Specifically, the correct tracking rates of the centroid distance histogram (CDH), angle distance vector (ADV) and proposed OORIM methods are 90.5%, 66.7%, and 100%, respectively.
Co-author:Liu Kui,Hu Huacan, An Bei, Mao Hongfei
Indexed by:Journal paper
Correspondence Author:Shen Peng
Discipline:Engineering
Document Type:J
Volume:21
Page Number:1-5
Translation or Not:no
Date of Publication:2024-06-24
Included Journals:SCI
Links to published journals:https://ieeexplore.ieee.org/document/10570475
Date of Publication:2024-06-24