Reliable search strategy for block motion estimation by measuring the error surface

The conventional search algorithms for block matching motion estimation reduce the set of possible displacements for locating the motion vector. Nearly all of these algorithms rely on the assumption: the distortion function increases monotonically as the search location moves away from the global minimum. Obviously, this assumption essentially requires that the error surface be unimodal over the search window. Unfortunately, this is usually not true in real-world video signals. In this paper, we formulate a criterion to check the confidence of unimodal error surface over the search window. The proposed Confidence Measure of Error Surface, CMES, would be a good measure for identifying whether the searching should continue or not. It is found that this proposed measure is able to strengthen the conventional fast search algorithms for block matching motion estimation. Experimental results show that, as compared to the conventional approach, the new algorithm through the CMES is more robust, produces smaller motion compensation errors, and requires simple computational complexity.