Gapfilling of optical images: principle
In this section, we propose to address a problem of image restoration, which is quite different in nature than land cover mapping, to show that deep learning can also be applied to other topics in remote sensing. For the practice session, using a GPU is strongly advised to reduce the processing time. We refer the reader to the OTBTF GitHub repository1 to get instructions for using the Docker image with GPU support.
A well-known issue impacting optical imagery is the presence of clouds. The need for cloud-free images at precise date is required in many operational monitoring applications. On the other hand, the SAR sensors are cloud-insensitive and they provide orthogonal ...
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