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Neural Network-Based Scalable Fast Intra Prediction Algorithm in H.264 Encoder

  • Jung-Hee Suk
  • Jin-Seon Youn
  • Jun Rim Choi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)

Abstract

In this paper, we propose a neural network-based scalable fast intra prediction algorithm in H.264 in order to reduce redundant calculation time by selecting the best mode of 4×4 and 16×16 intra prediction. In this reason, it is possible to encode compulsively by 4×4 intra prediction mode for current MB(macro block)’s best prediction mode without redundant mode decision calculation in accordance with neural network’s output resulted from co-relation of adjacent encoded four left, up-left, up and up-right blocks. If there is any one of MBs encoded by 16×16 intra prediction among four MBs adjacent to current MB, the probability of re-prediction into 16×16 intra prediction will become high. We can apply neural networks in order to decide whether to force into 4×4 intra prediction mode or not. We can also control both the bit rates and calculation time by modulating refresh factors and weights of neural network’s output depend on error back-propagation, which is called refreshing. In case of encoding several video sequences by the proposed algorithm, the total encoding time of 30 input I frames are reduced by 20% ~ 65% depending upon the test vector compared with JM 8.4 by using neural networks and by modulating scalable refreshing factor. On the other hand, total encoding bits are increased by 0.8% ~ 2.0% at the cost of reduced SNR of 0.01 dB.

Keywords

Mode Decision Prediction Mode Intra Prediction Reference Software Macro Block 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jung-Hee Suk
    • 1
  • Jin-Seon Youn
    • 1
  • Jun Rim Choi
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceKyungbook National UniversityDaeguKorea

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