Fig. 1: Overview of the model training cycle for the synthesis of low-quality images.
From: A deep learning framework for instrument-to-instrument translation of solar observation data
Images are transformed from the high-quality domain (B) to the low-quality domain (A) by generator G BA (yellow). The synthetic images are translated by generator G AB (blue) back to domain B. The mapping into domain A is enforced by discriminator D A, which is trained to distinguish between real images of domain A (bottom) and generated images (top). Both generators are trained jointly to fulfill the cycle consistency between original and reconstructed image, as well as for the generation of synthetic images that correspond to domain A. The generation of multiple low-quality versions from a single high-quality image is accomplished with the additional noise term that is added to generator BA.
