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Efficient Intra Mode Decision Via Statistical Learning

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4810))

Abstract

Intra mode selection and motion estimation for spatial and temporal prediction play important roles for achieving high video compression ratio in the latest video coding standards, such as H.264/AVC. However, both components take most of the computational cost in the video encoding process. In this paper, we propose an efficient intra mode prediction algorithm based on using the mode conditional probability learned from a large amount of training video sequences with the ground truth modes of each block to be encoded and its neighboring block modes as well as its associated image content features. By applying the proposed intra-mode selection algorithm into the H.264 reference code, we show significant reduction of the computation time with negligible video quality degradation for H.264 video encoding.

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References

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Authors and Affiliations

Authors

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Horace H.-S. Ip Oscar C. Au Howard Leung Ming-Ting Sun Wei-Ying Ma Shi-Min Hu

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© 2007 Springer-Verlag Berlin Heidelberg

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Hwang, C., Lai, SH. (2007). Efficient Intra Mode Decision Via Statistical Learning. In: Ip, H.HS., Au, O.C., Leung, H., Sun, MT., Ma, WY., Hu, SM. (eds) Advances in Multimedia Information Processing – PCM 2007. PCM 2007. Lecture Notes in Computer Science, vol 4810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77255-2_17

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  • DOI: https://doi.org/10.1007/978-3-540-77255-2_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77254-5

  • Online ISBN: 978-3-540-77255-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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