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FIMDA: A Fast Intra-frame Mode Decision Algorithm for MPEG-2/H.264 Transcoding

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3708))

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Abstract

The H.264 video compression standard provides tools for coding improvements of at least 2 dB, in terms of PSNR, and at least 50% in bit rate savings as compared with MPEG-2 video compression standard. It is expected that the H.264/MPEG-4 AVC will take over the digital video market, replacing the use of MPEG-2 in most digital video applications. The complete migration to the new video-coding algorithm will take several years given the wide scale use of MPEG-2 in the market place today. This creates an important need for transcoding technologies for converting the large volume of existent video material from the MPEG-2 into the H.264 format and vice versa. However, given the significant differences between the MPEG-2 and the H.264 encoding algorithms, the transcoding process of such systems is much more complex to other heterogeneous video transcoding processes. In this paper, we introduce and evaluate two versions of a fast intra-frame mode decision algorithm to be used as part of a high-efficient MPEG-2 to H.264 transcoder. In this work, we utilize an architecture of pixel domain video transcoding but we use the DC coefficient of the MPEG-2 DCT 8x8 blocks. Our evaluation results show that the proposed algorithm considerably reduces the complexity involved in the intra-frame prediction.

This work was supported by the Ministry of Science and Technology of Spain under CICYT project TIC2003-08154-C06-02, the Council of Science and Technology of Castilla-La Mancha under project PBC-03-001 and FEDER.

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© 2005 Springer-Verlag Berlin Heidelberg

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Fernández-Escribano, G., Cuenca, P., Orozco-Barbosa, L., Garrido, A. (2005). FIMDA: A Fast Intra-frame Mode Decision Algorithm for MPEG-2/H.264 Transcoding. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_54

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  • DOI: https://doi.org/10.1007/11558484_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29032-2

  • Online ISBN: 978-3-540-32046-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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