CONTRAST BOOST BY MACHINE LEARNING

A training system for a target machine learning model for image enhancement, and related methods. The system comprises a framework of two machine learning models (G1, G2) of the generative type, one such model (G1) being part of the target machine learning model. The training is based on a training data set including at least two types of training imagery, high image quality, IQ, imagery and low IQ imagery, the training input image (I) being one of the high IQ type. The generative network (G1) processes the training input image (I) of the high IQ type to produce a training output image (I) having reduced IQ. The target machine learning model (TM) further produces, based on the training output image (I) and the training input image (I) of the high IQ type, a second training output image (I). The second generator network (G2) estimates, from the second training output image (I), an estimate of the training input image of the high IQ type. A training controller (TC) adjusts parameters of the machine learning model framework, based a deviation between the estimate of the training input image of the high IQ type, and the said training input image (I) of the high IQ type.