RMSE: 0.049PSNR: 27.23SSIM: 0.859SAM: 10.168
Papers with Code · CC BY-SA 4.0
Cloud Removal
The majority of all optical observations collected via spaceborne satellites are affected by haze or clouds. Consequently, persistent cloud coverage affects the remote sensing practitioner's capabilities of a continuous and seamless monitoring of our planet. Cloud removal is the task of reconstructing cloud-covered information while preserving originally cloud-free details.
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논문
Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion
RMSE: 0.060PSNR: 26.04SSIM: 0.810SAM: 12.147
MAE: 0.043PSNR: 25.59SAM: 15.494SSIM: 0.764
MAE: 0.045PSNR: 24.78SAM: 18.085SSIM: 0.754
RMSE: 0.045PSNR: 28.07SSIM: 0.827SAM: 12.777
RMSE: 0.057PSNR: 25.42SSIM: 0.818SAM: 12.548
MAE: 0.045PSNR: 24.73SAM: 16.633SSIM: 0.701
MAE: 0.016PSNR: 33.17SAM: 4.840SSIM: 0.929
MAE: 0.019PSNR: 31.77SAM: 5.821SSIM: 0.902
MAE: 0.048PSNR: 25.14SAM: 15.676SSIM: 0.744
MAE: 0.028PSNR: 28.64SAM: 8.981SSIM: 0.885
RMSE: 0.051PSNR: 27.05SSIM: 0.849SAM: 11.649
MAE: 0.042PSNR: 25.87SAM: 14.788SSIM: 0.793
RMSE: 0.051PSNR: 26.68SSIM: 0.836SAM: 10.657