Method and data processing system for lossy image or video encoding, transmission and decoding

A method of training one or more neural networks, the one or more neural networks being for use in lossy image or video encoding, transmission and decoding, the method comprising the steps of:

• receiving a first input training image;
• encoding the first input training image using a first neural network to produce a latent representation;
• identifying one or more regions of the input image associated with high visual sensitivity;
• encoding the one or more regions of the input image associated with high visual sensitivity using a second trained neural network to produce one or more region latent representations;
• performing a quantization process on the latent representation and the one or more region latent representations;
• decoding the result of the quantization process to produce an output image, wherein the output image is an approximation of the input training image;
• evaluating a difference between the output image and the input training image;
• updating the parameters of the first neural network based on the evaluated difference;
• and
• repeating the above steps using a first set of training images to produce a first trained neural network.