Expert system based parallel multi-1D block matching algorithm with implementation for motion estimation

In this paper, we propose an expert-system based parallel multi-1-dimensional block matching algorithm (ESPM-1D-BMA) for motion estimation (ME). Instead of the conventional 2D block matching, we employ the parallel multi-1D blocks matching to improve the computing speed. To improve the ME accuracy, we design a knowledge base and inference engine to determine the true motion vector (MV) from the results of parallel multi-1D blocks matching. To speed up the computing speed further, we present a hardware architecture for implementing the ESPM-1D-BMA. We have demonstrated that the MV estimation accuracy achieved by the proposed ESPM-1D-BMA is much better than the comparing fast block matching algorithms and is close to the 2 dimensional full search block matching algorithm (2D-FSBMA). We also demonstrate that the computing speed of the proposed ESPM-1D-BMA is about two times as fast as the mixed-signal 2D-FSBMA (MS-2D-FSBMA).