Abstract
In order to reduce the complexity of MPEG-2 to H.264 transcoding, an efficient fast mode decision algorithm is proposed. We apply machine learning principles by building a decision tree (the relationship between the information gathered during the MPEG-2 decoding stage and the H.264 coding modes of MBs) enabling the development of very low complexity transcoding mechanism. The decision tree is used to determine the coding modes of the P-frames MBs of the output H.264 encoded video sequences. Experimental results show that the proposed algorithm can dramatically reduce the transcoding time, with high quality and high coding efficiency of image.
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