scholarly journals Performance Overview of the Latest Video Coding Proposals: HEVC, JEM and VVC

2021 ◽  
Vol 7 (2) ◽  
pp. 39
Author(s):  
Miguel O. Martínez-Rach ◽  
Héctor Migallón ◽  
Otoniel López-Granado ◽  
Vicente Galiano ◽  
Manuel P. Malumbres
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
State Of The Art ◽  
Rate Distortion ◽  
Video Content ◽  
Hardware Complexity ◽  
High Efficiency Video Coding ◽  
High Definition ◽  
The Cost ◽  
Performance Results

The audiovisual entertainment industry has entered a race to find the video encoder offering the best Rate/Distortion (R/D) performance for high-quality high-definition video content. The challenge consists in providing a moderate to low computational/hardware complexity encoder able to run Ultra High-Definition (UHD) video formats of different flavours (360°, AR/VR, etc.) with state-of-the-art R/D performance results. It is necessary to evaluate not only R/D performance, a highly important feature, but also the complexity of future video encoders. New coding tools offering a small increase in R/D performance at the cost of greater complexity are being advanced with caution. We performed a detailed analysis of two evolutions of High Efficiency Video Coding (HEVC) video standards, Joint Exploration Model (JEM) and Versatile Video Coding (VVC), in terms of both R/D performance and complexity. The results show how VVC, which represents the new direction of future standards, has, for the time being, sacrificed R/D performance in order to significantly reduce overall coding/decoding complexity.

scholarly journals Adaptive CU Split Decision Based on Deep Learning and Multifeature Fusion for H.266/VVC

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Jinchao Zhao ◽  
Yihan Wang ◽  
Qiuwen Zhang
Keyword(s):  
Deep Learning ◽  
Video Coding ◽  
High Efficiency ◽  
Texture Classification ◽  
Rate Distortion ◽  
Classification Model ◽  
High Efficiency Video Coding ◽  
Fast Encoding ◽  
Training Samples ◽  
Coding Unit

With the development of technology, the hardware requirement and expectations of user for visual enjoyment are getting higher and higher. The multitype tree (MTT) architecture is proposed by the Joint Video Experts Team (JVET). Therefore, it is necessary to determine not only coding unit (CU) depth but also its split mode in the H.266/Versatile Video Coding (H.266/VVC). Although H.266/VVC achieves significant coding performance on the basis of H.265/High Efficiency Video Coding (H.265/HEVC), it causes significantly coding complexity and increases coding time, where the most time-consuming part is traversal calculation rate-distortion (RD) of CU. To solve these problems, this paper proposes an adaptive CU split decision method based on deep learning and multifeature fusion. Firstly, we develop a texture classification model based on threshold to recognize complex and homogeneous CU. Secondly, if the complex CUs belong to edge CU, a Convolutional Neural Network (CNN) structure based on multifeature fusion is utilized to classify CU. Otherwise, an adaptive CNN structure is used to classify CUs. Finally, the division of CU is determined by the trained network and the parameters of CU. When the complex CUs are split, the above two CNN schemes can successfully process the training samples and terminate the rate-distortion optimization (RDO) calculation for some CUs. The experimental results indicate that the proposed method reduces the computational complexity and saves 39.39% encoding time, thereby achieving fast encoding in H.266/VVC.

scholarly journals Quality-Oriented Perceptual HEVC Based on the Spatiotemporal Saliency Detection Model

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 165 ◽  
Author(s):  
Xiantao Jiang ◽  
Tian Song ◽  
Daqi Zhu ◽  
Takafumi Katayama ◽  
Lu Wang
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Saliency Detection ◽  
Saliency Map ◽  
High Efficiency Video Coding ◽  
High Definition ◽  
Perceptual Coding ◽  
Coding Scheme ◽  
Saliency Model ◽  
Video Saliency

Perceptual video coding (PVC) can provide a lower bitrate with the same visual quality compared with traditional H.265/high efficiency video coding (HEVC). In this work, a novel H.265/HEVC-compliant PVC framework is proposed based on the video saliency model. Firstly, both an effective and efficient spatiotemporal saliency model is used to generate a video saliency map. Secondly, a perceptual coding scheme is developed based on the saliency map. A saliency-based quantization control algorithm is proposed to reduce the bitrate. Finally, the simulation results demonstrate that the proposed perceptual coding scheme shows its superiority in objective and subjective tests, achieving up to a 9.46% bitrate reduction with negligible subjective and objective quality loss. The advantage of the proposed method is the high quality adapted for a high-definition video application.

scholarly journals Enhanced Intra Prediction Based on Adaptive Coding Order and Multiple Reference Sets in HEVC

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 703
Author(s):  
Jin Young Lee
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Prediction Method ◽  
Rate Distortion ◽  
Spatial Prediction ◽  
Intra Prediction ◽  
High Efficiency Video Coding ◽  
Adaptive Coding ◽  
Advanced Video Coding ◽  
Multiple Reference

High Efficiency Video Coding (HEVC) is the most recent video coding standard. It can achieve a significantly higher coding performance than previous video coding standards, such as MPEG-2, MPEG-4, and H.264/AVC (Advanced Video Coding). In particular, to obtain high coding efficiency in intra frames, HEVC investigates various directional spatial prediction modes and then selects the best prediction mode based on rate-distortion optimization. For further improvement of coding performance, this paper proposes an enhanced intra prediction method based on adaptive coding order and multiple reference sets. The adaptive coding order determines the best coding order for each block, and the multiple reference sets enable the block to be predicted from various reference samples. Experimental results demonstrate that the proposed method achieves better intra coding performance than the conventional method.

Research on Key Algorithm of a New Generation Video Coding Standard HEVC

2013 ◽  
Vol 446-447 ◽  
pp. 961-965
Author(s):  
Gang Wang ◽  
He Xin Chen ◽  
Mian Shu Chen ◽  
Yuan Yuan Liu
Keyword(s):  
Video Coding ◽  
High Efficiency ◽  
Orthogonal Transformation ◽  
Basic Structure ◽  
Research Direction ◽  
Coding System ◽  
High Efficiency Video Coding ◽  
High Definition ◽  
High Definition Television ◽  
New Generation

The video coding standard of a new generation, high efficiency video coding ( HEVC ), is a video coding standard of JCT-VT under planning, mainly orienting toward high definition television （HDTV）and video coding system. From the start of the basic structure of HEVC, this paper not only introduces comprehensively the key HEVC technologies in intra-frame and inter-frame predictive estimation, orthogonal transformation, filter compensation and entropy coding but also points out the hot issues and the latest research direction.

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

2014 ◽  
Vol 3 ◽  
Author(s):  
Thaísa Leal da Silva ◽  
Luciano Volcan Agostini ◽  
Luis Alberto da Silva Cruz
Keyword(s):  
High Efficiency ◽  
Prediction Method ◽  
Rate Distortion ◽  
Low Complexity ◽  
Intra Prediction ◽  
High Efficiency Video Coding ◽  
Hierarchical Tree ◽  
The Cost ◽  
Encoding Efficiency ◽  
Hierarchical Tree Structure

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).

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