Classified variable block size motion estimation algorithm for image sequence coding

In recent years, the variable block size (VBS) motion estimation technique has been widely employed to improve the performance of the block matching algorithm (BMA). In VBS, the block size is varied according to the type of motion. The VBS is known to be very efficient for areas containing complex motions. But, it requires a large amount of computation. The computation required is 2 or 5 times compared with the full search BMA. In this paper, a new VBS motion estimation algorithm, called the classified variable block size (CVBS), is proposed to overcome this problem. The algorithm classifies the input blocks into 3 categories: the background, the shade-motion, and the edge-motion. According the characteristics of the classified blocks, various motion estimation techniques are then used to improve the coding performance. The performance of VBS and CVBS under the coding efficiency is investigated. It is shown that the CVBS algorithm requires about 1/6 to 1/10 computations needed by the conventional VBS algorithm