Research On High Efficiency Coding Technologies For H.264/AVC

With the development of digitalization process, people put forward higher requirements on the quality of video. The HD resolution and high frame rate videos are widely used in digital TV, video monitoring and network broadcasting. In recent years, with the development of new multimedia business and mobile communication technology, people are eager to realize the real-time HD video communication on the mobile terminal. The video coding technology has solved the problem of limited transmission bandwidth. However, the processing data increases dramatically when coding the HD video, and also presenting a great challenge for the system with limited source, especially the mobile terminal with limited battery. And, because keen competition in the industry, even for the digital TV and security monitoring, the design companies are constantly introducing new solutions to reduce the implementation cost, and enhance competitiveness.H.264/AVC is the main coding format standard used in Blu-ray DVD and IPTV, which has higher compression efficiency and huge computation complexity. Based on the existing coding technology, we focus on the efficient coding technology to further reduce the computational complexity of the encoding process. The main works and achievements are as follows:(1) Research on the intra coding process. The coding mode selection algorithm and prediction mode selection algorithm are two ways to improve intra coding efficiency. In coding mode selection algorithm, the pixels are used as basic unit to compute the flatness characteristic of coding block, but large amount of calculations are needed in this process. Accordingly, a fats intra-coding mode decision algorithm is proposed, which is based on the distribution of the mean value on44sub-blocks. When compared with other algorithms, this algorithm can effectively reduce the amount of computation of the flatness characteristic process. The SAD has a regular structure and can be easily implement by hardware. But all pixels in the block and predicted pixels of each mode are needed to calculate, which result in excess calculation. Accordingly, a fast prediction mode selection algorithm based on the partial SAD is also proposed. The key pixels of each prediction mode are defined, and the prediction modes are categorized into several groups according with the difference of key pixels. Base on this difference, the calculation process of SAD can be simplified, and the calculation of predicted pixels also can be avoided. The coding results and hardware implementation show that, compared with other algorithms, this algorithm has less prediction mode and lower hardware costs. (2) Research on the inter coding process. The coding speed of inter prediction can be accelerate by using motion correlation of spatial and temporal neighbor macro blocks. However, in the video sequences with complex motion activity, the correlations between the adjacent macro blocks became weakly, and then lead to a decline in the acceleration of the coding speed. To accurately measure the motion complexity of MB, a fast inter-prediction mode decision algorithm is presented, which is based on the moving complexity in the reference region. The reference region is used to evaluate the motion characteristic, and the coding modes are classified into several categories according to the movement complexity. Extensive test results show that the proposed algorithm can reduce the overall encoding time by70%on average compared with the original algorithm in the H.264/AVC standard codec. Compared with other algorithms, especially for video sequences motion complexity, this algorithm can obtain a higher coding speed. The hardware implementation also results show that the algorithm is simple and easy to implement.(3) Research on the search range adjustment (SR) algorithm. At present, only several fixed predetermined SR are used in most search range adjustment algorithm, so the adaptive ability of these algorithms is not high. Because the search range is mainly determined by the predicted motion vector (PMV), the algorithm which is based on the probability density function of motion vector difference can obtain better motion estimation performance, but the calculation process of it is too complex. According to this, this paper presents search range adjustment algorithm which is based on the accuracy of PMV. In this algorithm, a simple measurement is defined to evaluate the accuracy the PMV, and SR is adaptively adjusted by using the relationship between the SR and the accuracy of PMV. The motion vectors of the coding region are also analyzed, the consistency of motion vectors are used to further reduce the SR size. Test results show, the number of search points can be reduced to2.15%when using our algorithm, and compared to the UMHexagonS algorithm,15%motion estimation time can be saved.(4) Research on search the multiple reference frame decision algorithm. The top-down prediction method can give the number of candidate reference frame, so it can give higher coding efficiency. But for the test sequence with complex motion, prediction accuracy is not high, and the number of reference frame is also increasing. In this paper, the correlations between the reference frames of different block partitions are analyzed. And the conclusion are drawn that the higher accuracy and less reference frames can be gotten when using the bottom block partitions. Then a fast multiframe selection algorithm is proposed, which is based on the88block partition. According to the relationship between the different partitions, the reference frames of each partition are predicted by using the88partition. Experimental results proved, when applying our algorithm, the reference frame numbers can be reduced from5to1.25. Compared to other typical algorithms, our algorithm obtains a much reduction in the coding time, with the same bit rate and PSNR.