Fast CU size decision and mode decision algorithm for HEVC intra coding

The emerging international standard of High Efficiency Video Coding (HEVC) is a successor to H.264/AVC. In the joint model of HEVC, the tree structured coding unit (CU) is adopted, which allows recursive splitting into four equally sized blocks. At each depth level, it enables up to 34 intra predict...

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Bibliographic Details
Published in:IEEE transactions on consumer electronics 2013-02, Vol.59 (1), p.207-213
Main Authors: Shen, Liquan, Zhang, Zhaoyang, An, Ping
Format: Article
Language:English
Subjects:
Accuracy
Algorithm design and analysis
Algorithms
Coding
Complexity
Computation
Computational complexity
Correlation
Encoding
HEVC
intra prediction
Mathematical models
mode decision
Prediction algorithms
Skips
Studies
Video coding
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Summary:The emerging international standard of High Efficiency Video Coding (HEVC) is a successor to H.264/AVC. In the joint model of HEVC, the tree structured coding unit (CU) is adopted, which allows recursive splitting into four equally sized blocks. At each depth level, it enables up to 34 intra prediction modes. The intra mode decision process in HEVC is performed using all the possible depth levels and prediction modes to find the one with the least rate distortion (RD) cost using Lagrange multiplier. This achieves the highest coding efficiency but requires a very high computational complexity. In this paper, we propose a fast CU size decision and mode decision algorithm for HEVC intra coding. Since the optimal CU depth level is highly content-dependent, it is not efficient to use a fixed CU depth range for a whole image. Therefore, we can skip some specific depth levels rarely used in spatially nearby CUs. Meanwhile, there are RD cost and prediction mode correlations among different depth levels or spatially nearby CUs. By fully exploiting these correlations, we can skip some prediction modes which are rarely used in the parent CUs in the upper depth levels or spatially nearby CUs. Experimental results demonstrate that the proposed algorithm can save 21% computational complexity on average with negligible loss of coding efficiency.
ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2013.6490261