Bayesian adaptive algorithm for fast coding unit decision in the High Efficiency Video Coding (HEVC) standard

The latest High Efficiency Video Coding standard (HEVC) provides a set of new coding tools to achieve a significantly higher coding efficiency than previous standards. In this standard, the pixels are first grouped into Coding Units (CU), then Prediction Units (PU), and finally Transform Units (TU)....

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Vydané v:Signal processing. Image communication Ročník 56; s. 1 - 11
Hlavní autori: Jiménez-Moreno, Amaya, Martínez-Enríquez, Eduardo, Díaz-de-María, Fernando
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier B.V 01.08.2017
Elsevier BV
Predmet:
Adaptive algorithms
Algorithms
Bayesian analysis
Bayesian statistics
Coding
Complexity
Complexity reduction
Computation
Efficiency
Fast coding unit decision
High Efficiency Video Coding
Hypothesis test
Image coding
On the fly estimation
Parameter estimation
Signal processing
Video
Video compression
Hypothesis test
Complexity reduction
High Efficiency Video Coding
Bayesian statistics
On the fly estimation
Fast coding unit decision
ISSN:0923-5965, 1879-2677
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Shrnutí:The latest High Efficiency Video Coding standard (HEVC) provides a set of new coding tools to achieve a significantly higher coding efficiency than previous standards. In this standard, the pixels are first grouped into Coding Units (CU), then Prediction Units (PU), and finally Transform Units (TU). All these coding levels are organized into a quadtree-shaped arrangement that allows highly flexible data representation; however, they involve a very high computational complexity. In this paper, we propose an effective early CU depth decision algorithm to reduce the encoder complexity. Our proposal is based on a hierarchical approach, in which a hypothesis test is designed to make a decision at every CU depth, where the algorithm either produces an early termination or decides to evaluate the subsequent depth level. Moreover, the proposed method is able to adaptively estimate the parameters that define each hypothesis test, so that it adapts its behavior to the variable contents of the video sequences. The proposed method has been extensively tested, and the experimental results show that our proposal outperforms several state-of-the-art methods, achieving a significant reduction of the computational complexity (36.5% and 38.2% average reductions in coding time for two different encoder configurations) in exchange for very slight losses in coding performance (1.7% and 0.8% average bit rate increments). •An effective early CU depth decision algorithm to reduce the encoder complexity is proposed.•A hypothesis test based on Bayesian statistics is designed to make a decision at every CU depth in a hierarchical way.•The statistical parameters are updated on the fly to the changing content of the sequence achieving an adaptive design.•R-D costs are employed as features to make accurate early decisions on the CU depth.
Bibliografia:ObjectType-Article-1
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ISSN:0923-5965
1879-2677
DOI:10.1016/j.image.2017.04.004