Motion vector correction based on the pattern-like image analysis

In this paper, we propose a motion vector correction algorithm to correct the erroneous motion vectors due to the failure of conventional motion estimation (ME) based on block matching algorithm (BMA). The proposed method is based on the pattern-like image analysis that consists of the periodic pattern detection and calculation of motion parameters for the motion vector correction. In addition, the proposed method corrects effectively the erroneous motion vectors using the relations between the periodic pattern and local/global minima depending on whether the periodic pattern is static or moving. Also, it does not significantly increase computational complexity since it uses the estimated motion vectors and the integral projection of the sum of absolute difference (SAD) previously obtained from the conventional ME. Experimental results indicate good performance of the proposed scheme with significant reduction the erroneous motion vectors.