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Fast CU size decision and PU mode decision algorithm in HEVC intra coding

Authors: Xiwu Shang; Guozhong Wang; Tao Fan; Yan Li;

Fast CU size decision and PU mode decision algorithm in HEVC intra coding

Abstract

High Efficiency Video Coding (HEVC) is a new video compression standard for high resolution video content, which only needs 50% bit rate of the H.264/AVC at the same perceptual quality. However, high computational complexity increases dramatically for adopting quad-tree structured Coding Unit (CU). In this paper, a fast CU size decision and Prediction Unit (PU) mode decision algorithm is presented for HEVC intra coding. It exploits the depth information of neighboring CUs to make an early CU split decision or CU pruning decision. Moreover, there are correlations between the higher layer prediction mode and current layer mode in PUs. By using these correlations, we can terminate some prediction modes which are rarely selected as the optimal mode. Experimental results illustrate that the proposed method can save 37.91% computational complexity on average as compared with the current HM with only 0.66% increase in BDBR and 0.03 dB loss in BDPSNR.

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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!
42
Top 10%
Top 10%
Top 10%
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