摘要
In this letter, an improved three-step search algorithm is presented, which uses both gray and chromatic information to boost the performance with random optimization and converge the motion vectors to global optima. Experimental results show that this algorithm can efficiently improve the PSNR after motion compensation.
In this letter, an improved three-step search algorithm is presented, which uses both gray and chromatic information to boost the performance with random optimization and converge the motion vectors to global optima. Experimental results show that this algorithm can efficiently improve the PSNR after motion compensation.
