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Non-Cloud Sentinel-2 Images via GAN by marcos is a document available to read on EtoBox.
This study introduces a new data fusion model, the Multi-channels Conditional Generative Adversarial Network (MCcGAN), to generate cloud-free Sentinel-2-like images using Sentinel-1 data. The model addresses the issue of cloud contamination in optical satellite images by leveraging the capabilities of Synthetic Aperture Radar (SAR) to provide reliable surface feature information. Experimental results demonstrate that the MCcGAN outperforms existing methods in generating high-quality simulated Sentinel-2 ima
- Author
- marcos
- Language
- EN