The current high efficiency video coding (HEVC) standard is developed to achieve greatly improved compression performance compared with the previous coding standard H.264/AVC. It adopts a quadtree based picture partition structure to flexibility signal various texture characteristics of images. However, this results in a dramatic increase in computational complexity, which obstructs HEVC in real-time application. To alleviate this problem, we propose a fast coding unit (CU) size decision algorithm in HEVC intra coding based on consideration of the depth level of neighboring CUs, distribution of rate distortion (RD) value and distribution of residual data. Experimental results demonstrate that the proposed algorithm can achieve up to 60% time reduction with negligible RD performance loss.
Tao FAN
Shanghai University
Guozhong WANG
Shanghai University
Xiwu SHANG
Shanghai University
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Tao FAN, Guozhong WANG, Xiwu SHANG, "Fast Coding Unit Size Decision in HEVC Intra Coding" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 7, pp. 1953-1956, July 2016, doi: 10.1587/transinf.2015EDL8231.
Abstract: The current high efficiency video coding (HEVC) standard is developed to achieve greatly improved compression performance compared with the previous coding standard H.264/AVC. It adopts a quadtree based picture partition structure to flexibility signal various texture characteristics of images. However, this results in a dramatic increase in computational complexity, which obstructs HEVC in real-time application. To alleviate this problem, we propose a fast coding unit (CU) size decision algorithm in HEVC intra coding based on consideration of the depth level of neighboring CUs, distribution of rate distortion (RD) value and distribution of residual data. Experimental results demonstrate that the proposed algorithm can achieve up to 60% time reduction with negligible RD performance loss.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2015EDL8231/_p
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@ARTICLE{e99-d_7_1953,
author={Tao FAN, Guozhong WANG, Xiwu SHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Fast Coding Unit Size Decision in HEVC Intra Coding},
year={2016},
volume={E99-D},
number={7},
pages={1953-1956},
abstract={The current high efficiency video coding (HEVC) standard is developed to achieve greatly improved compression performance compared with the previous coding standard H.264/AVC. It adopts a quadtree based picture partition structure to flexibility signal various texture characteristics of images. However, this results in a dramatic increase in computational complexity, which obstructs HEVC in real-time application. To alleviate this problem, we propose a fast coding unit (CU) size decision algorithm in HEVC intra coding based on consideration of the depth level of neighboring CUs, distribution of rate distortion (RD) value and distribution of residual data. Experimental results demonstrate that the proposed algorithm can achieve up to 60% time reduction with negligible RD performance loss.},
keywords={},
doi={10.1587/transinf.2015EDL8231},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - Fast Coding Unit Size Decision in HEVC Intra Coding
T2 - IEICE TRANSACTIONS on Information
SP - 1953
EP - 1956
AU - Tao FAN
AU - Guozhong WANG
AU - Xiwu SHANG
PY - 2016
DO - 10.1587/transinf.2015EDL8231
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2016
AB - The current high efficiency video coding (HEVC) standard is developed to achieve greatly improved compression performance compared with the previous coding standard H.264/AVC. It adopts a quadtree based picture partition structure to flexibility signal various texture characteristics of images. However, this results in a dramatic increase in computational complexity, which obstructs HEVC in real-time application. To alleviate this problem, we propose a fast coding unit (CU) size decision algorithm in HEVC intra coding based on consideration of the depth level of neighboring CUs, distribution of rate distortion (RD) value and distribution of residual data. Experimental results demonstrate that the proposed algorithm can achieve up to 60% time reduction with negligible RD performance loss.
ER -