ADAPTIVE DISTORTION-BASED PARTIAL DISTORTION SEARCH FOR FAST MOTION ESTIMATION

Abstract

Block motion estimation with full search is computationally complex. To reduce this complexity, different methods have been proposed, including partial distortion, which can reduce the computational complexity with no loss of image quality. We propose a Distortion-based Partial Distortion Search (DPDS) based on the magnitude of distortion and adaptive update of the matching order. We calculate absolute differences for all pixels in the predicted block point. Pixels are then sorted by the amount of distortion in a descending order for the matching process, which produces a scanning map. The Sum of the Absolute Differences (SAD) of other candidate positions is then computed from this matching order. We also use an update of the scanning map by checking the increase in the number of absolute differences for the SAD value. The proposed DPDS algorithm improves the computational efficiency, compared with the original PDS scheme, because the accumulated value of the absolute pixel differences can rapidly reach the current minimum SAD value. The proposed algorithm is 4-13 times faster than the full search method with the same visual quality.