APSIPA Transactions on Signal and Information Processing > Vol 3 > Issue 1

HEVC intra prediction acceleration based on texture direction and prediction unit modes reuse

Thaísa Leal da Silva, University of Coimbra, Portugal, thaisa.silva@co.it.pt , Luciano Volcan Agostini, Federal University of Pelotas, Brazil, Luis Alberto da Silva Cruz, University of Coimbra, Portugal
 
Suggested Citation
Thaísa Leal da Silva, Luciano Volcan Agostini and Luis Alberto da Silva Cruz (2014), "HEVC intra prediction acceleration based on texture direction and prediction unit modes reuse", APSIPA Transactions on Signal and Information Processing: Vol. 3: No. 1, e13. http://dx.doi.org/10.1017/ATSIP.2014.14

Publication Date: 05 Dec 2014
© 2014 Thaísa Leal da Silva, Luciano Volcan Agostini and Luis Alberto da Silva Cruz
 
Subjects
 
Keywords
Intra prediction, HEVC, Computational complexity, Edge orientation, Inter-levels correlation
 

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Journal details

Open Access

This is published under the terms of the Creative Commons Attribution licence.

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In this article:
I. INTRODUCTION 
II. INTRA PREDICTION IN HEVC 
III. RELATED WORKS 
IV. INTRA MODE DECISION ACCELERATION ALGORITHM 
V. RESULTS AND COMPARISONS 
VI. CONCLUSIONS 

Abstract

The new High Efficiency Video Coding (HEVC) standard achieves higher encoding efficiency when compared to its predecessors such as H.264/AVC. One of the factors responsible for this improvement is the new intra prediction method, which introduces a larger number of prediction directions resulting in an enhanced rate-distortion (RD) performance obtained at the cost of higher computational complexity. This paper proposes an algorithm to accelerate the intra mode decision, reducing the complexity of intra coding. The acceleration procedure takes into account the texture local directionality information and explores the correlation of intra modes across levels of the hierarchical tree structure used in HEVC. Experimental results show that the proposed algorithm provides a decrease of 39.22 and 43.88% in the HEVC intra prediction processing time on average, for all-intra high efficiency (AI-HE) and low complexity (AI-LC) configurations, respectively, with a small degradation in encoding efficiency (BD-PSNR loss of 0.1 dB for AI-HE and 0.8 dB for AI-LC on average).

DOI:10.1017/ATSIP.2014.14