TY - JOUR
T1 - Two-Stage Fast Inter CU Decision for HEVC Based on Bayesian Method and Conditional Random Fields
AU - Zhang , Jia
AU - Kwong, Sam
AU - Wang, Xu
PY - 2018/11
Y1 - 2018/11
N2 - In the latest video coding standard High Efficiency Video Coding (HEVC), a quadtree-based Coding Unit (CU) partitioning scheme is adopted to better adapt to the characteristics of the video contents. However, the flexible scheme significantly increases the coding complexity because large amount of possible CU partitioning modes should be traversed. In this paper, we propose a two-stage fast inter CU decision method to reduce the coding complexity of the HEVC encoders. In Stage I, all the CUs are classified into three categories based on Bayesian method after the Prediction Unit (PU) mode merge 2N ×2N is checked. Early CU pruning and early CU skipping are then applied to two of the categories, respectively. For the remaining category which is difficult to differentiate by the Rate-Distortion (RD) cost of the PU mode merge 2N × 2N, an early CU pruning scheme based on Conditional Random Fields (CRFs) is performed in Stage II, which takes both the local characteristics of the current CU and the coding information of its neighboring CUs into consideration. Experimental results show that our method can reduce 54.93% and 45.84% of the coding complexity on average with only 1.19% and 1.03% Bjontegaard Delta bitrate increment under the Random Access (RA) main and the Low Delay P (LDP) configurations, respectively.
AB - In the latest video coding standard High Efficiency Video Coding (HEVC), a quadtree-based Coding Unit (CU) partitioning scheme is adopted to better adapt to the characteristics of the video contents. However, the flexible scheme significantly increases the coding complexity because large amount of possible CU partitioning modes should be traversed. In this paper, we propose a two-stage fast inter CU decision method to reduce the coding complexity of the HEVC encoders. In Stage I, all the CUs are classified into three categories based on Bayesian method after the Prediction Unit (PU) mode merge 2N ×2N is checked. Early CU pruning and early CU skipping are then applied to two of the categories, respectively. For the remaining category which is difficult to differentiate by the Rate-Distortion (RD) cost of the PU mode merge 2N × 2N, an early CU pruning scheme based on Conditional Random Fields (CRFs) is performed in Stage II, which takes both the local characteristics of the current CU and the coding information of its neighboring CUs into consideration. Experimental results show that our method can reduce 54.93% and 45.84% of the coding complexity on average with only 1.19% and 1.03% Bjontegaard Delta bitrate increment under the Random Access (RA) main and the Low Delay P (LDP) configurations, respectively.
KW - Bayes methods
KW - Bayesian method
KW - Complexity theory
KW - conditional random fields
KW - Copper
KW - CU decision
KW - Encoding
KW - High efficiency video coding
KW - High Efficiency Video Coding (HEVC)
KW - Training
UR - http://www.scopus.com/inward/record.url?scp=85029156208&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85029156208&origin=recordpage
U2 - 10.1109/TCSVT.2017.2747618
DO - 10.1109/TCSVT.2017.2747618
M3 - RGC 21 - Publication in refereed journal
SN - 1051-8215
VL - 28
SP - 3223
EP - 3235
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 11
ER -