Systems and methods for adjustable image rescaling

Abstract

Presented herein are embodiments of systems and methods for training a system and for using a trained system to generate super-resolution imagery from low-resolution imagery. Embodiments for generating super-resolution imagery from low-resolution imagery include obtaining an input trade-off parameter that indicates a preference regarding low distortion or high perceptual quality for a generated SR image and obtaining a latent variable from a distribution defined, at least in part, by a trade-off parameter. Embodiments include inputting an LR image and the latent variable into an embodiment of an invertible rescaling network (IRNN) in an inverse upscaling direction of the IRNN to generate an output SR image that comprises accuracy and perception qualities conditioned by the input trade-off parameter. In one or more embodiments, a trained IRNN uses a trade-off parameter that indicates a desired trade-off between whether the trained IRNN generates an SR image having lower distortion or higher perceptual quality.