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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/73167


    Title: A Fast Intra Prediction Based on Haar Transform in H.264/AVC
    Authors: Yen, Shwu-Huey;Lin, meng-ju;Hwan, shin-jia;Li, tai-kuang
    Contributors: 淡江大學資訊工程學系
    Keywords: H.264/AVC;Haar transform;Intra predictio
    Date: 2009-12
    Issue Date: 2011-10-24 11:35:17 (UTC+8)
    Publisher: Taipei : Institute of electrical and electronics engineers (IEEE)
    Abstract: H.264/AVC is one of the state of the art in video compressing standards. It has advantages of low bit-rate and high image quality. However, the omplexity of H.264/AVC encoder limits applications in the real time video communication. In this study, a fast intra prediction with Haar transform algorithm (FIPHTA) is proposed to simplify the complexity of luma intra prediction. For each luma macroblock (MB), a Haar transform is first executed. By observing LL coefficients, this MB will be classified as 16-MB, I4-MB, or both. An I16-MB indicates that this MB is smooth and only Intra 16×16 (I16) prediction modes are to be considered. An I4-MB indicates that this MB is textured and only Intra 4×4 (I4) prediction modes are to be considered. And the rest of MBs (both) have to consider both prediction modes as in the standard H.264/AVC. Next, to choose an I16 prediction mode for a MB, the vertical and horizontal energies of the LL coefficients are calculated to reduce candidate modes. Similarly, the pixel-based vertical and horizontal energies are calculated for a 4×4 block to reduce I4 candidate modes. The simulation showed that the proposed algorithm can maintain the similar mode selection results comparing to the full search algorithm of H.264 but with a remarkable computation deduction.
    Relation: Proceedings of the 2009 joint conferences on pervasive computing, pp.161-166
    DOI: 10.1109/JCPC.2009.5420195
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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