SSR-GAN: super resolution-based generative adversarial networks model for flood image enhancement
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-03269-z.pdf
Reference48 articles.
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3. Tong, X., Luo, X., Liu, S., Xie, H., Chao, W., Liu, S., Liu, S., Makhinov, A.N., Makhinova, A.F., Jiang, Y.: An approach for flood monitoring by the combined use of Landsat 8 optical imagery and Cosmo-skymed radar imagery. ISPRS J. Photogramm. Remote. Sens. 136, 144–153 (2018). https://doi.org/10.1016/j.isprsjprs.2017.11.006
4. Mason, D.C., Speck, R., Devereux, B., Schumann, G.J.-P., Neal, J.C., Bates, P.D.: Flood detection in urban areas using terrasar-X. IEEE Trans. Geosci. Remote Sens. 48, 882–894 (2010). https://doi.org/10.1109/tgrs.2009.2029236
5. Ponmani, E., Saravanan, P.: Image denoising and despeckling methods for SAR images to improve image enhancement performance: a survey. Multimed. Tool. Appl. 80, 26547–26569 (2021). https://doi.org/10.1007/s11042-021-10871-7
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