b
Corresponding author: yfw@shu.edu.cn
A fast CU size decision algorithm for 3D-HEVC
Yubing Wang
1,a
, Yongfang Wang
2,b
and Yawen Shi
3,c
1
Shanghai University, Shanghai, China
2
Shanghai University, Shanghai, China
3
Shanghai University, Shanghai, China
Abstract. The emerging 3D-HEVC has achieved the highest coding efficiency but requires a very high computational
complexity. To speed up the encoding process for the dependent texture views, we propose a fast CU depth range
selection algorithm by jointly making use of the inter-view and temporal-spatial correlations. Firstly, adaptive
correlation weights are proposed to predict coding unit(CU) depth range and skip some specific depth levels rarely
used in independent view, the previous frame and neighboring CUs. Besides, a new early termination algorithm is
proposed to further reduce the coding time. Experimental results demonstrate that the proposed method saves about
56% coding time on average compared to HTM with maintaining the similar video quality.
1 Introduction
With the rapid development of multimedia technology,
compared to text, voice, images, video is used more and
more abroad. However, the traditional 2D video can't
meet people's need, and 3D video is becoming more and
more popular. It is well known that the data size of video
is huge, so it asks for higher requirement for transferring,
storing and playing. Furthermore, 3D video uses more
than one camera to shoot the same scene, which leads to
increasing a large amount of information.
To improve the coding efficiency of high-definition
video, the Joint Collaborative Team on Video Coding
(JCT-VC) designs the standard High Efficiency Video
Coding (HEVC)[1]. Subsequently, the Joint
Collaborative Team on 3D Video Coding Extension
Development (JCT-3V) develops HEVC based 3D video
coding standard (3D-HEVC), which is for the
compression of multi view video plus depth (MVD)
format[2]. In 3D-HEVC, similar to HEVC, the mode
decision process in HTM is performed using all the
possible CU sizes , prediction modes, and coding
tools(disparity-compensated prediction (DCP), inter-view
motion prediction, backward view synthesis prediction
(BVSP)) to find the optimal one with the least rate
distortion (RD) cost using Lagrange multiplier, which
leads to high computational workloads. It obstructs wide
application of 3D-HEVC.
In order to reduce the complexity of video coding,
much work has been done to explore the fast algorithms
for H.264/AVC. Liu et al.[3] propose block partition
algorithm based on image features to reduce the coding
complexity. The low complexity mode prediction in [4] is
proposed based on the spatial-temporal correlation. The
algorithm in [5] uses SKIP mode to early terminate mode
decision. Fast algorithms for HEVC inter prediction
mainly aim at the process of coding unit (CU) selection
which has high complexity. Method in [6] is proposed to
terminate procedures of CU splitting by setting a
threshold value based on the RD-cost of the CUs which
have already been coded, if the RD-cost of the current
CU is less than this threshold ,CU will stop splitting, and
a fast CU size decision method based on coding tree
pruning is proposed in [7]. Shen et al.[8] propose three
early termination methods based on motion homogeneity
checking, RD cost checking and SKIP mode checking to
skip the procedure of motion estimation on unnecessary
small CU sizes. In 3D-HEVC, the maximum depth of the
related coding block in dependent view is first used to
early terminate the CU splitting in [10]. A fast mode
decision algorithm based on variable size CU and
disparity estimation in [11] is proposed to reduce 3D-
HEVC computational complexity. The texture quad-tree
initialization (QTI) and depth quad-tree limitation (QTL)
coding tools and their associated predictive coding (PC)
algorithm by utilizing the correlations between the quad-
tree of the texture and its associated depth is proposed in
[12], which was adopted by the 3D-HEVC working draft.
Zhang et al.[13] speed up the encoding process of
dependent texture views based on inter-view correlation,
which uses an early merge mode decision algorithm and
an early CU splitting termination algorithm. CU depth
correlation between the independent view and the
dependent view is also studied to accelerate CU splitting
process of dependent views in [14].
The aforementioned methods for 3D video coding
only use view correlation or temporal-spatial correlation
to predict the depth of current coding block, while not
jointly considering these correlations. Consequently, in
this paper, we comprehensively exploited the correlations
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