recently, while watching a video about machine learning, I had an idea about creating an image compression algorithm, that works similar to JPEG, but is based on arbitrary bitmaps as blocks.
I should mention that I would not call myself a computer scientist, so my understanding of the math and algorithms involved are still limited at this point. I have an intuition for how deconstructing an image into blocks, which are represented as combinations of 8x8 px patterns (made up of cosine waves) works.
so my question is: is it possible to replace the standard JPEG patterns with something else? -- for instance the features that have been found by a neural network (see below).
I'd be very interested in what the results / artifacts of such a compression would look like, both applied to the original data set (the neural net was trained on) and random other images.
any ideas / directions on how to achieve this are very much appreciated.
thanks a lot in advance!