Can somebody explain to me why the Horn and Schunck algorithm (probably mostly the smoothness constraint) is robust to image sequences that are quantized rather coarsely in space and/or time. (Thought that is only the case when I use a multi-resolution approach) Also it is insensitive to additive noise and quantization of brightness levels. It calculates the optic flow with a Laplacian of the flow velocities so that the complete image should have an effect on each image gradient vector. But isn't this a reason that the algorithm is robust to these characteristics?
Please provide a detailed explanation. If i've made mistakes by explaining my problem please point it out, this method is still very difficult for me to understand in detail.