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DOI: 10.14569/IJACSA.2016.071042
PDF

Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics

Author 1: Kanayah Saurty
Author 2: Pierre C. Catherine
Author 3: Krishnaraj M. S. Soyjaudah

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 10, 2016.

  • Abstract and Keywords
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Abstract: High Efficiency Video Coding (HEVC) or H.265 is currently the latest standard in video coding. While this new standard promises improved performance over the previous H.264/AVC standard, the complexity has drastically increased due to the various new improved tools added. The splitting of the 64x64 Largest Coding Unit (LCU) into smaller CU sizes forming a quad tree structure involves a significant number of operations and comparisons which imposes a high computational burden on the encoder. In addition, the improved Motion Estimation (ME) techniques used in HEVC inter prediction in order to ensure greater compression also contribute to the high encoding time. In this paper, a set of standard thresholds are identified based on the Mean Square (MS) of the residuals. These thresholds are used to terminate the CU splitting process and to skip some of the inter modes processing. In addition, CUs with large MS values are split at a very early stage. Experimental results show that the proposed method can effectively reduce the encoding time by 62.2% (70.8% for ME) on average, compared to HM 10, yielding a BD-Rate of only 1.14%.

Keywords: HEVC; inter prediction; early termination scheme; complexity reduction; prediction residuals

Kanayah Saurty, Pierre C. Catherine and Krishnaraj M. S. Soyjaudah, “Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics” International Journal of Advanced Computer Science and Applications(IJACSA), 7(10), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071042

@article{Saurty2016,
title = {Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071042},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071042},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {10},
author = {Kanayah Saurty and Pierre C. Catherine and Krishnaraj M. S. Soyjaudah}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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