Paper
9 December 2021 A sea ice extraction method that fuses coherence and amplitude information and combines pixel-level and object-level methods
Author Affiliations +
Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290Z (2021) https://doi.org/10.1117/12.2625594
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China
Abstract
Fast and accurate sea ice detection is of great significance to the natural environmental protection of the sea and the development of the marine economy. With the development of satellite remote sensing technology, sea ice detection based on high-resolution SAR images has received wide attention. Given the serious pretzel phenomenon of image-level classification results and the limitation of object-level classification by segmentation scale, this study proposes a sea ice extraction method based on the coherence and magnitude information of TanDEM-X images and combining image level and object level. The method was compared with the sea ice extraction results of the traditional method, and the results showed that the overall accuracy, user accuracy, product accuracy, and Kappa coefficient of this newly constructed sea ice extraction method improved 38.74%, 19.43%, 37.48% and 0.7597, respectively, compared with the traditional extraction method, which significantly improved the sea ice extraction accuracy.
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Ping Ni, Kai Tang, and Zhiyong Wang "A sea ice extraction method that fuses coherence and amplitude information and combines pixel-level and object-level methods", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290Z (9 December 2021); https://doi.org/10.1117/12.2625594
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KEYWORDS
Image segmentation

Image classification

Synthetic aperture radar

Coherence (optics)

Data acquisition

Feature extraction

Image processing algorithms and systems

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