Probably because of how bloody large they are. The quantization errors likely cancel each other out over the sum of so many terms.

Same reason why you can get a pretty good reconstruction when you add random noise to an image and then apply a binary threshold function to it. The more pixels there are, the more recognizable will be the B&W reconstruction.