Complexity Control Based on a Fast Coding Unit Decision Method in the HEVC Video Coding Standard
TL;DR: An effective complexity control (CC) algorithm based on a hierarchical approach that is able to achieve a target complexity reduction of up to 60% with respect to full exploration, with notable accuracy and limited losses in coding performance is proposed.
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Abstract: The emerging high-efficiency video coding standard achieves higher coding efficiency than previous standards by virtue of a set of new coding tools such as the quadtree coding structure. In this novel structure, the pixels are organized into coding units (CU), prediction units, and transform units, the sizes of which can be optimized at every level following a tree configuration. These tools allow highly flexible data representation; however, they incur a very high computational complexity. In this paper, we propose an effective complexity control (CC) algorithm based on a hierarchical approach. An early termination condition is defined at every CU size to determine whether subsequent CU sizes should be explored. The actual encoding times are also considered to satisfy the target complexity in real time. Moreover, all parameters of the algorithm are estimated on the fly to adapt its behavior to the video content, the encoding configuration, and the target complexity over time. The experimental results prove that our proposal is able to achieve a target complexity reduction of up to 60 $\%$ with respect to full exploration, with notable accuracy and limited losses in coding performance. It was compared with a state-of-the-art CC method and shown to achieve a significantly better trade-off between coding complexity and efficiency as well as higher accuracy in reaching the target complexity. Furthermore, a comparison with a state-of-the-art complexity reduction method highlights the advantages of our CC framework. Finally, we show that the proposed method performs well when the target complexity varies over time.
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Figures

Fig. 3. Flowchart of the proposed method. 
Fig. 4. An illustration of the pdfs for several R-D costs at CU depth 0 for two sequences, “BasketballDrill” and “FourPeople”. 
TABLE II MEANS AND STANDARD DEVIATIONS OF THE R-D COSTS ASSOCIATED WITH EVERY PU MODE WHEN DEPTH 0 IS OPTIMAL AND WHEN IT IS NOT. ![TABLE IV PERFORMANCE EVALUATION OF THE PROPOSED METHOD IN COMPARISON WITH [11].](/figures/table-iv-performance-evaluation-of-the-proposed-method-in-2p3fbsxf.png)
TABLE IV PERFORMANCE EVALUATION OF THE PROPOSED METHOD IN COMPARISON WITH [11]. 
Fig. 6. R-D performance for the 4 considered target complexities for the sequence BasketballPass. 
Fig. 7. R-D performance for the 4 considered target complexities for the sequence BQTerrace.
Citations
CTU-Level Complexity Control for High Efficiency Video Coding
TL;DR: A novel complexity control scheme for high efficiency video coding (HEVC) is proposed by dynamically adjusting the depth range for each coding tree unit (CTU) and has superior complexity control accuracy and complexity control stability compared with other one-pass complexity control strategies.
48
Online Learning-Based Multi-Stage Complexity Control for Live Video Coding
TL;DR: An online learning-based multi-stage complexity control method for live video coding that outperforms the state-of-the-art algorithms in terms of both accuracy of complexity control and RD performance.
29
A Spatiotemporal Content-Based CU Size Decision Algorithm for HEVC
TL;DR: An efficient and fast CU size decision algorithm is proposed to reduce HEVC encoder complexity by the spatiotemporal features and can achieve an average 59.73% and 64.98% reduction in encoding time along with a 0.68% and 1.27% Bjontegaard Delta bitrate penalty.
25
Complexity Control in the HEVC Intracoding for Industrial Video Applications
TL;DR: A feedback-based error elimination scheme removes the complexity error during the encoding process and the rate-distortion performance and complexity control accuracy of the proposed method are superior to those of the state-of-the-art methods.
25
Saliency-Guided Complexity Control for HEVC Decoding
TL;DR: A saliency-guided complexity control approach for HEVC decoding, which reduces the decoding complexity to the target with minimal perceptual quality loss and the experimental results validate the effectiveness of this approach.
References
Overview of the High Efficiency Video Coding (HEVC) Standard
TL;DR: The main goal of the HEVC standardization effort is to enable significantly improved compression performance relative to existing standards-in the range of 50% bit-rate reduction for equal perceptual video quality.
Generalized Lagrange Multiplier Method for Solving Problems of Optimum Allocation of Resources
TL;DR: The use of Lagrange multipliers for optimization in the presence of constraints is not limited to differentiable functions but can be applied to problems of maximizing an arbitrary real valued objective function over any set whatever, subject to bounds on the values of any other finite collection of real valued functions denned on the same set as mentioned in this paper.
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