There are 2000 reference restored images and 6003 original underwater images in the unpaired training set.
Unsupervised image-to-image translation tasks aim to find a mapping between a source domain X and a target domain Y from unpaired training data.
Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world.
Additionally, to the best of our knowledge, our method is the first specialized method to super-resolve mosaic images, whether it be multi-spectral or Bayer.
This mosaic image is then merged with the mosaic image generated by the SR network to produce a quantitatively superior image.
This paper introduces a novel method to simultaneously super-resolve and colour-predict images acquired by snapshot mosaic sensors.
This paper introduces a newly collected and novel dataset (StereoMSI) for example-based single and colour-guided spectral image super-resolution.