Application of the motion vector constraint to the regularized enhancement of compressed video
We present a novel fidelity constraint for the image enhancement problem by exploiting the motion vectors of a compressed video bit-stream. These vectors establish a correspondence between image pixels across a series of frames, and our goal is to maintain this relationship during processing. In our past work, we considered algorithms that relied on the sum-of-absolute differences as the match criteria. As we show in this paper, this metric is problematic for the enhancement problem. We then pose the constraint within the context of a sum-of-squared errors criterion for matching. This allows for a more rigorous treatment of the fidelity constraint. Finally, experimental results illustrate the performance of the new constraint.