A New Method of Video Transcoding Using Adaptive Motion Estimation
一种自适应运动估值视频代码转换的新方法

To the video signal transmission on narrow band networks, this paper analyzes the quality degradation that cause the non optimized motion vectors during the traditional video transcoding when the frame rate conversion. We proposed a model of adaptive motion vectors based on the sum of the differential quantization errors, thus reduced search area. It is possible to achieve fast motion estimation for near optimal outgoing motion vectors. Based on the gray system theory, an efficient gray prediction search(GPS) algorithm for block motion estimation is proposed. The GPS can determine the motion vectors of image blocks quickly and correctly. We speed up the encoding in further using a method of adaptive fast video encoding based on the theoretical model for discrete cosine transform(DCT) coefficients. We also present a fast DCT algorithm to speed up the calculation of DCT further when the quantization step size is large. The experimental result show that the proposed scheme improves the video quality, with a minimal increase in computational complexity.