The way many compressors work is based on recent data, they try to predict immediately following data. The prediction doesn't have to be perfect; it just has to

The way many compressors work is based on recent data, they try to predict immediately following data. The prediction doesn't have to be perfect; it just has to be good enough that only the difference between the prediction and the exact data needs to be encoded, and encoding that delta usually takes fewer bits than encoding the original data. The compression scheme here is similar. Transmit a low res version of an image, use a neural network to guess what a 2x size image would look like, then send just the delta to fix where the prediction was wrong. Then do it again until the final resolution image is reached. If the neural network is terrible, you'd still get a lossless image recovery, but the amount of data sent in deltas would be greater than just sending the image uncompressed.