generate a bunch of variations as usual, potentially at a range of noise levels
either tag each image with the noise level it was sampled at, or (fancier more expensive version) compute inter-image similarities to form a transition matrix
tie the driving signal to the noise level the image was sampled at, or to transition similarity (fun constrained optimization here)