Polarimetric Synthetic-Aperture-Radar Change-Type Classification with a Hyperparameter-Free Open-Set Classifier
Abstract
Synthetic aperture radar (SAR) is a remote sensing technology that can truly operate 24/7. It's an all-weather system that can operate at any time except in the most extreme conditions. Coherent change detection (CCD) in SAR can identify minute changes such as vehicle tracks that occur between images taken at different times. From polarimetric SAR capabilities, researchers have developed decompositions that allow one to automatically classify the scattering type in a single polarimetric SAR (PolSAR) image set. We extend that work to CCD in PolSAR images to identify the type change. Such as change caused by no return regions, trees, or ground. This work could then be used as a preprocessor for algorithms to automatically detect tracks.
Cite
Text
Koch et al. "Polarimetric Synthetic-Aperture-Radar Change-Type Classification with a Hyperparameter-Free Open-Set Classifier." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00170Markdown
[Koch et al. "Polarimetric Synthetic-Aperture-Radar Change-Type Classification with a Hyperparameter-Free Open-Set Classifier." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/koch2018cvprw-polarimetric/) doi:10.1109/CVPRW.2018.00170BibTeX
@inproceedings{koch2018cvprw-polarimetric,
title = {{Polarimetric Synthetic-Aperture-Radar Change-Type Classification with a Hyperparameter-Free Open-Set Classifier}},
author = {Koch, Mark W. and West, R. Derek and Riley, Robert and Quach, Tu-Thach},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2018},
pages = {1239-1246},
doi = {10.1109/CVPRW.2018.00170},
url = {https://mlanthology.org/cvprw/2018/koch2018cvprw-polarimetric/}
}