GEWDiff Training & Evaluation Dataset 📘 Overview The GEWDiff Training & Evaluation Dataset is derived from the EnMAP Champion and MDAS hyperspectral datasets. It is designed for image enhancement, super resolution, restoration, and generative remote sensing tasks. The dataset includes Low Quality (LQ) low resolution images, corresponding Ground Truth (GT) high resolution images, and optional structure information such as masks and edges (partially provided; remaining components can be automatically generated using the accompanying GitHub scripts). All data have been preprocessed, spatially tiled, spectrally unified, and harmonized through nearest neighbor approximation of the spectral response functions (SRF) . 📂 Dataset Structure 1. Training Set LQ images : low quality / low resolution observations GT images : high quality ground truth targets Mask (partial) : missing parts can be generated with included scripts Edge (partial) : missing parts can be generated with included scripts Used for model training across various reconstruction and generative tasks. 2. Validation Set (val) Same structure as the training set Paired LQ–GT samples for model validation and tuning 3. Test Sets…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy