Super-resolving multiresolution images with band-independant geometry of multispectral pixels
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A new resolution enhancement method is presented for multispectral and multi-resolution images, such as these provided by the Sentinel-2 satellites. Starting from the highest resolution bands, band-dependent information (reflectance) is separated from information that is common to all bands (geometry of scene elements). This model is then applied to unmix low-resolution bands, preserving their reflectance, while propagating band-independent information to preserve the sub-pixel details. A reference implementation is provided, with an application example for super-resolving Sentinel-2 data.
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Cited by 1 Pith paper
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Super-Resolution of PROBA-V Images Using Convolutional Neural Networks
A CNN performs multi-image super-resolution on PROBA-V data and reports higher PSNR than bicubic upscaling for most scenes.
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