1. CCESAR: Coastline Classification-Extraction From SAR Images Using CNN-U-Net Combination
- Author
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Arora, Vidhu, Gupta, Shreyan, Kudupu, Ananthakrishna, Priyadarshi, Aditya, Mundayatt, Aswathi, and Sreevalsan-Nair, Jaya
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
In this article, we improve the deep learning solution for coastline extraction from Synthetic Aperture Radar (SAR) images by proposing a two-stage model involving image classification followed by segmentation. We hypothesize that a single segmentation model usually used for coastline detection is insufficient to characterize different coastline types. We demonstrate that the need for a two-stage workflow prevails through different compression levels of these images. Our results from experiments using a combination of CNN and U-Net models on Sentinel-1 images show that the two-stage workflow, coastline classification-extraction from SAR images (CCESAR) outperforms a single U-Net segmentation model.
- Published
- 2025