hvn2/S2S_UCNN
Official Python codes for the paper "Sentinel-2 Sharpening Using a Single Unsupervised Convolutional Neural Network With MTF-Based Degradation Model", published in IEEE JSTARS Vol. 14, 2021.
This tool helps scientists and analysts working with satellite imagery to enhance the detail in their Sentinel-2 multispectral images. It takes the standard Sentinel-2 bands, including the lower-resolution 20m and 60m bands, and outputs sharpened versions of these bands, making them appear as if they were captured at a higher 10m resolution. This is particularly useful for earth observation specialists, environmental researchers, and urban planners.
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Use this if you need to improve the spatial resolution of your Sentinel-2 imagery for more detailed analysis without relying on traditional, often less accurate, sharpening methods.
Not ideal if you are working with satellite data other than Sentinel-2 or if you prefer methods that require extensive manual tuning and separate training for different resolution bands.
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Oct 19, 2022
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