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Despite the several speedup methods proposed in the literature, the computational complexity of High Efficiency Video Coding (HEVC) video encoding is still a problem. This paper proposes a fast coding unit (CU) partition decision for use in HEVC encoders based on support vector machine (SVM)-trained offline. The SVM classifiers, features, and training procedures are described in detail, and a justification for the use of SVMs is provided. The trained classifiers are incorporated into a modified reference encoder in the form of a fast CU partition decision algorithm, which decides if the exhaustive search for the best partition is continued or terminated prematurely. Using the proposed method, an average complexity reduction of 48% is achieved with a 0.48% Bjontegaard-Delta bitrate (BD-BR) loss using the random access coding configuration, 44% reduction with a 0.62% BD-BR loss for the Low Delay B, and a 41% reduction with a 0.6% BD-BR loss for the Low Delay P configuration. We also tested our approach under constant bitrate conditions, achieving a 47% reduction in encoding time with a 1.11% loss in the BD-BR. In addition, a decision threshold adaptation is also proposed to allow adjusting the rate-distortion/complexity trade-off of our solution. With this approach, the computational complexity reduction can be varied from 34.9% (with a 0.13% loss in the BD-BR) up to 52.4% (with a 1.11% BD-BR loss) using the random access configuration. Compared with the state-of-the-art solutions, our decision scheme outperforms the related works in terms of combined rate distortion and complexity. [ABSTRACT FROM AUTHOR]

Several different methods have been investigated in recent years, aiming at computational complexity reduction and scaling of High Efficiency Video Coding (HEVC) software implementations. However, maintaining the encoding time per frame or group of pictures (GOPs) below an adjustable upper bound is still an open research issue. A solution for this problem is devised in this paper based on a set of Pareto-efficient encoding configurations, identified through rate-distortion-complexity analysis. The proposed method combines a medium-granularity encoding time control with a fine-granularity encoding time control to accurately limit the HEVC encoding time below a predefined target for each GOP. It is shown that the encoding time can be kept below a desired target for a wide range of encoding time reductions, e.g., up to 90% in comparison with the original encoder. The results also show that compression efficiency loss (Bjøntegaard delta-rate) varies from negligible (0.16%) to moderate (9.83%) in the extreme case of 90% computational complexity reduction. [ABSTRACT FROM AUTHOR]

The High Efficiency Video Coding standard provides improved compression ratio in comparison with its predecessors at the cost of large increases in the encoding computational complexity. An important share of this increase is due to the new flexible partitioning structures, namely the coding trees, the prediction units, and the residual quadtrees, with the best configurations decided through an exhaustive rate-distortion optimization (RDO) process. In this paper, we propose a set of procedures for deciding whether the partition structure optimization algorithm should be terminated early or run to the end of an exhaustive search for the best configuration. The proposed schemes are based on decision trees obtained through data mining techniques. By extracting intermediate data, such as encoding variables from a training set of video sequences, three sets of decision trees are built and implemented to avoid running the RDO algorithm to its full extent. When separately implemented, these schemes achieve average computational complexity reductions (CCRs) of up to 50% at a negligible cost of 0.56% in terms of Bjontegaard Delta (BD) rate increase. When the schemes are jointly implemented, an average CCR of up to 65% is achieved, with a small BD-rate increase of 1.36%. Extensive experiments and comparisons with similar works demonstrate that the proposed early termination schemes achieve the best rate-distortion-complexity tradeoffs among all the compared works. [ABSTRACT FROM AUTHOR]

This paper presents a performance evaluation study of coding efficiency versus computational complexity for the forthcoming High Efficiency Video Coding (HEVC) standard. A thorough experimental investigation was carried out to identify the tools that most affect the encoding efficiency and computational complexity of the HEVC encoder. A set of 16 different encoding configurations was created to investigate the impact of each tool, varying the encoding parameter set and comparing the results with a baseline encoder. This paper shows that, even though the computational complexity increases monotonically from the baseline to the most complex configuration, the encoding efficiency saturates at some point. Moreover, the results of this paper provide relevant information for implementation of complexity-constrained encoders by taking into account the tradeoff between complexity and coding efficiency. It is shown that low-complexity encoding configurations, defined by careful selection of coding tools, achieve coding efficiency comparable to that of high-complexity configurations. [ABSTRACT FROM PUBLISHER]