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Adaptive Quad-tree Complexity Control for HEVC

Authors: Kun Duan; Pengyu Liu 0001; Kebin Jia; Zeqi Feng; Zhonghua Sun 0003;

Adaptive Quad-tree Complexity Control for HEVC

Abstract

To reduce the computational complexity of High Efficiency Video Coding (HEVC), this paper proposed an adaptive quad-tree complexity control mechanism. The proposed mechanism first defines similar region flag (SRF) to distinguish between similar region and non-similar region. Then, two algorithms, similar region depth range prediction algorithm and non-similar region depth range prediction algorithm, are proposed. The similar region depth range prediction algorithm estimates the feature of similar region based on coding unit (CU) depth of this region. The optimal depth of this region can be predicted. The non-similar region depth range prediction algorithm can skip low probability tree nodes based on depth correlation coefficient (DCC), which is calculated based on scene content change. Experimental results show that the pro-posed mechanism can reduce computational complexity by 28.17% on average with 0.75% Bjontegaard delta bit rate (BDBR) increase and 0.03dB Bjontegaard delta peak signal-to-noise rate (BDPSNR) drop under random access (RA) con-figuration. For low delay (LD) configuration, it can reduce complexity by 32.99% with 1.98% BDBR increase and 0.06dB BDPSNR drop penalty. The proposed mechanism is expected to be applied in the real-time environments.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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