Fast Interframe mode decision algorithm based on mode mapping and MB activity for MPEG-2 to H.264/AVC transcoding

Recently the latest video coding standard H.264/AVC is widely used for the mobile and low bitrate video codec in the various multimedia terminals. On the other hand, the MPEG-2 MP@HL codec has become the center of digital video contents since it is the standard codec for the Digital TV (DTV). To provide the bridge between the contents in MPEG-2 and mobile terminals, the transcoding of MPEG-2 contents into H.264/AVC format is an inevitable technology in the digital video market. The main bottleneck in the process lies in the computational complexity. In H.264/AVC, the variable block size (VBS) mode decision (MID) is used in the Interframe for the improved performance in the motion compensated prediction. For the macroblock (MB) which cannot be accurately predicted with one motion vector (MV), it is partitioned into smaller blocks and predicted with different MVs. In addition, SKIP and Intra modes are also permitted in the Interframe MID of H.264/AVC to further ameliorate the encoding performance. With the VBS MD technology, the Inter prediction accuracy can be improved significantly. However, the incidental side-effect is the high computational complexity. In this paper, we propose a fast Interframe MID algorithm for MPEG-2 to H.264/AVC transcoding. The relationships between SKIP and Intra modes are detected at first to map these two kinds of modes directly from MPEG-2 to H.264/AVC. And then the MB activity will be scaled by the residual DCT energy obtained from the MPEG-2 decoding process to estimate the block sizes of the MB mode for H.264/AVC Interframe MD. In our proposed method, the original redundant candidate modes can be eliminated effectively, resulting in the reduction of the computational complexity. It can reduce about 85% Rate-to-Distortion Cost (RDCost) computing and 45% entire processing time compared with the well-known cascaded transcoder while maintaining the video quality. (C) 2009 Elsevier Inc. All rights reserved.