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Efficient Mode Selection with BMA Based Pre-processing Algorithms for H.264/AVC Fast Intra Mode Decision

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Advances in Multimedia Modeling (MMM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6523))

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Abstract

In a H.264/AVC intra-frame encoder, the complicated computations for the mode decision cause the difficulty in real-time applications. In this paper, we propose an efficient fast algorithm, which is called Block Matching Algorithm (BMA), to predict the best direction mode for the fast intra mode decision. The edge detective technique can predict luma-4x4, luma-16x16, and chroma-8x8 modes directly. The BMA method uses the relations between the current block and the predictive block to predict edge directions. We can partition the intra prediction procedure into two steps. At the first step, we use the pre-processing mode selection algorithms to find the primary mode which can be selected for fast prediction. At the second step, the selected fewer high-potential candidate modes are applied to calculate the RD cost for the mode decision. The encoding time is largely reduced, and meanwhile we also maintain the same video quality. Simulation results show that the proposed BMA method reduces the encoding time by 75%, and requires bit-rate increase about 2.5% and peak signal-to-noise ratio (PSNR) decrease about 0.07 dB in QCIF and CIF sequences, compared with the H.264/AVC JM 14.2 software. Our methods can achieve less PSNR degradation and bit-rate increase than the previous methods with more encoding time reduction.

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References

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© 2011 Springer-Verlag Berlin Heidelberg

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Miao, CH., Fan, CP. (2011). Efficient Mode Selection with BMA Based Pre-processing Algorithms for H.264/AVC Fast Intra Mode Decision. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_2

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  • DOI: https://doi.org/10.1007/978-3-642-17832-0_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17831-3

  • Online ISBN: 978-3-642-17832-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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