Implicit motion compensated noise reduction of motion video scenes

Signals derived from video systems which generate motion picture scenes possess a great deal of temporal redundancy. The temporal correlation of adjacent frames is often completely determined by the displacement field, which over the course of time traces out the motion trajectories of moving objects within the scene. It is possible to exploit the available redundancy in these signals for the purpose of noise reduction by compensating for the presence of motion. We present an adaptive filtering technique which implicitly compensates for motion within a scene by performing 1-D signal estimation along a set of hypothesized motion directions. This technique adapts the estimator parameters to the local image characteristics along a set of specified directions in the 3-D signal space. Experiments with real life scenes have shown that this method achieves substantial noise reduction in many cases, while preserving the edge contrast of the desired signal.