Abstract
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. However, it requires a large number of computations. In this article, 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 three categories: background, shade motion and edge motion. According to the characteristics of the classified blocks, various motion estimation techniques are then used to improve the coding performance. The performance of VBS and CVBS based on the coding efficiency is investigated. It is shown that the CVBS algorithm requires about one fifth to one seventh of the computations needed by the conventional VBS algorithm. © 1996 John Wiley & Sons, Inc.
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