Journal articles on the topic 'VVC, Versatile Video Coding'
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1
Silva, Giovane Gomes, Ícaro Gonçalves Siqueira, Mateus Grellert, and Claudio Machado Diniz. "Approximate Hardware Architecture for Interpolation Filter of Versatile Video Coding." Journal of Integrated Circuits and Systems 16, no. 2 (August 15, 2021): 1–8. http://dx.doi.org/10.29292/jics.v16i2.327.
Abstract:
The new Versatile Video Coding (VVC) standard was recently developed to improve compression efficiency of previous video coding standards and to support new applications. This was achieved at the cost of an increase in the computational complexity of the encoder algorithms, which leads to the need to develop hardware accelerators and to apply approximate computing techniques to achieve the performance and power dissipation required for systems that encode video. This work proposes the implementation of an approximate hardware architecture for interpolation filters defined in the VVC standard targeting real-time processing of high resolution videos. The architecture is able to process up to 2560x1600 pixels videos at 30 fps with power dissipation of 23.9 mW when operating at a frequency of 522 MHz, with an average compression efficiency degradation of only 0.41% compared to default VVC video encoder software configuration.
2
Choi, Kiho. "A Study on Fast and Low-Complexity Algorithms for Versatile Video Coding." Sensors 22, no. 22 (November 20, 2022): 8990. http://dx.doi.org/10.3390/s22228990.
Abstract:
Versatile Video Coding (VVC)/H.266, completed in 2020, provides half the bitrate of the previous video coding standard (i.e., High-Efficiency Video Coding (HEVC)/H.265) while maintaining the same visual quality. The primary goal of VVC/H.266 is to achieve a compression capability that is noticeably better than that of HEVC/H.265, as well as the functionality to support a variety of applications with a single profile. Although VVC/H.266 has improved its coding performance by incorporating new advanced technologies with flexible partitioning, the increased encoding complexity has become a challenging issue in practical market usage. To address the complexity issue of VVC/H.266, significant efforts have been expended to develop practical methods for reducing the encoding and decoding processes of VVC/H.266. In this study, we provide an overview of the VVC/H.266 standard, and compared with previous video coding standards, examine a key challenge to VVC/H.266 coding. Furthermore, we survey and present recent technical advances in fast and low-complexity VVC/H.266, focusing on key technical areas.
3
Zouidi, Naima, Amina Kessentini, Wassim Hamidouche, Nouri Masmoudi, and Daniel Menard. "Multitask Learning Based Intra-Mode Decision Framework for Versatile Video Coding." Electronics 11, no. 23 (December 2, 2022): 4001. http://dx.doi.org/10.3390/electronics11234001.
Abstract:
In mid-2020, the new international video coding standard, namely versatile video coding (VVC), was officially released by the Joint Video Expert Team (JVET). As its name indicates, the VVC enables a higher level of versatility with better compression performance compared to its predecessor, high-efficiency video coding (HEVC). VVC introduces several new coding tools like multiple reference lines (MRL) and matrix-weighted intra-prediction (MIP), along with several improvements on the block-based hybrid video coding scheme such as quatree with nested multi-type tree (QTMT) and finer-granularity intra-prediction modes (IPMs). Because finding the best encoding decisions is usually preceded by optimizing the rate distortion (RD) cost, introducing new coding tools or enhancing existing ones requires additional computations. In fact, the VVC is 31 times more complex than the HEVC. Therefore, this paper aims to reduce the computational complexity of the VVC. It establishes a large database for intra-prediction and proposes a multitask learning (MTL)-based intra-mode decision framework. Experimental results show that our proposal enables up to 30% of complexity reduction while slightly increasing the Bjontegaard bit rate (BD-BR).
4
Amrutha Valli Pamidi, Lakshmi, and Purnachand Nalluri. "Optimized in-loop filtering in versatile video coding using improved fast guided filter." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (February 1, 2024): 911. http://dx.doi.org/10.11591/ijeecs.v33.i2.pp911-919.
Abstract:
<p>Devices with varying display capabilities from a common source may face degradation in video quality because of the limitation in transmission bandwidth and storage. The solution to overcome this challenge is to enrich the video quality. For the mentioned purpose, this paper introduces an improved fast guided filter (IFGF) for the contemporary video coding standard H.266/VVC (versatile video coding), a continuation of H.265/HEVC (high efficiency video coding). VVC includes several types of coding techniques to enhance video coding efficiency over existing video coding standards. Despite that, blocking artifacts are still present in the images. Hence, the proposed method focuses on denoising the image and the increase of video quality, which is measured in terms of peak signal-to-noise (PSNR). The objective is achieved by using an IFGF for in-loop filtering in VVC to denoise the reconstructed images. VTM (VVC test model)-17.2 is used to simulate the various video sequences with the proposed filter. This method achieves a 0.67% Bjontegaard delta (BD)-rate reduction in low-delay configuration accompanied by an encoder run time increase of 4%.</p>
5
Jung, Seongwon, and Dongsan Jun. "Context-Based Inter Mode Decision Method for Fast Affine Prediction in Versatile Video Coding." Electronics 10, no. 11 (May 24, 2021): 1243. http://dx.doi.org/10.3390/electronics10111243.
Abstract:
Versatile Video Coding (VVC) is the most recent video coding standard developed by Joint Video Experts Team (JVET) that can achieve a bit-rate reduction of 50% with perceptually similar quality compared to the previous method, namely High Efficiency Video Coding (HEVC). Although VVC can support the significant coding performance, it leads to the tremendous computational complexity of VVC encoder. In particular, VVC has newly adopted an affine motion estimation (AME) method to overcome the limitations of the translational motion model at the expense of higher encoding complexity. In this paper, we proposed a context-based inter mode decision method for fast affine prediction that determines whether the AME is performed or not in the process of rate-distortion (RD) optimization for optimal CU-mode decision. Experimental results showed that the proposed method significantly reduced the encoding complexity of AME up to 33% with unnoticeable coding loss compared to the VVC Test Model (VTM).
6
高啟洲, 高啟洲, and 賴美妤 Chi-Chou Kao. "基於深度學習之改良式多功能影像編碼快速畫面內模式決策研究." 理工研究國際期刊 12, no. 1 (April 2022): 037–48. http://dx.doi.org/10.53106/222344892022041201004.
Abstract:
<p>H.266/Versatile Video Coding (VVC) 是針對 4K 以上的超高畫質影片，且能適用在高動態範圍(High Dynamic Range Imaging, HDR)及廣色域(wide color gamut, WCG)中，但基於四元樹加二元樹(Quadtree plus Binary Tree, QTBT)的編碼單元(Coding Unit, CU)結構增加了 H.266/VVC 編碼的計算複雜性。本論文提出了一種基於深度學習之改良式多功能影像編碼快速畫面內模式決策方法，減少 H.266/VVC 內編碼複雜性以加快H.266/VVC 的編碼速度，並將畫面內影像編碼結合卷積神經網路(Convolutional Neural Networks, CNN)在 H.266/VVC 畫面內編碼的模式預測決策，以達到比原始編碼方式(JEM7.0)更好的編碼效能。</p> <p> </p><p>H.266/VVC is ultra-high-definition video over 4K, and can be applied in High Dynamic Range Imaging (HDR) and wide color gamut (WCG). However, it has high coding computational complexity based on the coding unit (CU) structure of a quadtree plus binary tree (QTBT). This plan first proposes a fast coding unit spatial features decision method to reduce the coding complexity in H.266/VVC such that the H.266/VVC coding can be speed up. Another important contribution of this plan is to combine video coding with Convolutional Neural Networks (CNNs) in H.266/VVC in-frame coding mode prediction decision. It can be shown that the proposed methods can achieve better encoding performance than the original encoding method (JEM7.0).</p> <p> </p>
7
Mishra, Amit Kumar. "Versatile Video Coding (VVC) Standard: Overview and Applications." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 10, no. 2 (September 10, 2019): 975–81. http://dx.doi.org/10.17762/turcomat.v10i2.13578.
Abstract:
Information security includes picture and video compression and encryption since compressed data is more secure than uncompressed imagery. Another point is that handling data of smaller sizes is simple. Therefore, efficient, secure, and simple data transport methods are created through effective data compression technology. Consequently, there are two different sorts of compression algorithm techniques: lossy compressions and lossless compressions. Any type of data format, including text, audio, video, and picture files, may leverage these technologies. In this procedure, the Least Significant Bit technique is used to encrypt each frame of the video file format to be able to increase security. The primary goals of this procedure are to safeguard the data by encrypting the frames and compressing the video file. Using PSNR to enhance process throughput would also enhance data transmission security while reducing data loss.
8
Li, Minghui, Zhaohong Li, and Zhenzhen Zhang. "A VVC Video Steganography Based on Coding Units in Chroma Components with a Deep Learning Network." Symmetry 15, no. 1 (December 31, 2022): 116. http://dx.doi.org/10.3390/sym15010116.
Abstract:
Versatile Video Coding (VVC) is the latest video coding standard, but currently, most steganographic algorithms are based on High-Efficiency Video Coding (HEVC). The concept of symmetry is often adopted in deep neural networks. With the rapid rise of new multimedia, video steganography shows great research potential. This paper proposes a VVC steganographic algorithm based on Coding Units (CUs). Considering the novel techniques in VVC, the proposed steganography only uses chroma CUs to embed secret information. Based on modifying the partition modes of chroma CUs, we propose four different embedding levels to satisfy the different needs of visual quality, capacity and video bitrate. In order to reduce the bitrate of stego-videos and improve the distortion caused by modifying them, we propose a novel convolutional neural network (CNN) as an additional in-loop filter in the VVC codec to achieve better restoration. Furthermore, the proposed steganography algorithm based on chroma components has an advantage in resisting most of the video steganalysis algorithms, since few VVC steganalysis algorithms have been proposed thus far and most HEVC steganalysis algorithms are based on the luminance component. Experimental results show that the proposed VVC steganography algorithm achieves excellent performance on visual quality, bitrate cost and capacity.
9
Saha, Anup, Miguel Chavarrías, Fernando Pescador, Ángel M. Groba, Kheyter Chassaigne, and Pedro L. Cebrián. "Complexity Analysis of a Versatile Video Coding Decoder over Embedded Systems and General Purpose Processors." Sensors 21, no. 10 (May 11, 2021): 3320. http://dx.doi.org/10.3390/s21103320.
Abstract:
The increase in high-quality video consumption requires increasingly efficient video coding algorithms. Versatile video coding (VVC) is the current state-of-the-art video coding standard. Compared to the previous video standard, high efficiency video coding (HEVC), VVC demands approximately 50% higher video compression while maintaining the same quality and significantly increasing the computational complexity. In this study, coarse-grain profiling of a VVC decoder over two different platforms was performed: One platform was based on a high-performance general purpose processor (HGPP), and the other platform was based on an embedded general purpose processor (EGPP). For the most intensive computational modules, fine-grain profiling was also performed. The results allowed the identification of the most intensive computational modules necessary to carry out subsequent acceleration processes. Additionally, the correlation between the performance of each module on both platforms was determined to identify the influence of the hardware architecture.
10
Chen, Guojie, and Min Lin. "Sample-Based Gradient Edge and Angular Prediction for VVC Lossless Intra-Coding." Applied Sciences 14, no. 4 (February 18, 2024): 1653. http://dx.doi.org/10.3390/app14041653.
Abstract:
Lossless coding is a compression method in the Versatile Video Coding (VVC) standard, which can compress video without distortion. Lossless coding has great application prospects in fields with high requirements for video quality. Since the current VVC standard is mainly designed for lossy coding, the compression efficiency of VVC lossless coding makes it hard to meet people’s needs. In order to improve the performance of VVC lossless coding, this paper proposes a sample-based intra-gradient edge detection and angular prediction (SGAP) method. SGAP utilizes the characteristics of lossless intra-coding to employ samples adjacent to the current sample as reference samples and performs prediction through sample iteration. SGAP aims to improve the prediction accuracy for edge regions, smooth regions and directional texture regions in images. Experimental results on the VVC Test Model (VTM) 12.3 reveal that SGAP achieves 7.31% bit-rate savings on average in VVC lossless intra-coding, while the encoding time is only increased by 5.4%. Compared with existing advanced sample-based intra-prediction methods, SGAP can provide significantly higher coding performance gain.
11
Li, Ximei, Jun He, Qi Li, and Xingru Chen. "An Adjacency Encoding Information-Based Fast Affine Motion Estimation Method for Versatile Video Coding." Electronics 11, no. 21 (October 23, 2022): 3429. http://dx.doi.org/10.3390/electronics11213429.
Abstract:
Versatile video coding (VVC), a new generation video coding standard, achieves significant improvements over high efficiency video coding (HEVC) due to its added advanced coding tools. Despite the fact that affine motion estimation adopted in VVC takes into account the translational, rotational, and scaling motions of the object to improve the accuracy of interprediction, this technique adds a high computational complexity, making VVC unsuitable for use in real-time applications. To address this issue, an adjacency encoding information-based fast affine motion estimation method for VVC is proposed in this paper. First, this paper counts the probability of using the affine mode in interprediction. Then we analyze the trade-off between computational complexity and performance improvement based on statistical information. Finally, by exploring the mutual exclusivity between skip and affine modes, an enhanced method is proposed to reduce interprediction complexity. Experimental results show that compared with the VVC, the proposed low-complexity method achieves 10.11% total encoding time reduction and 40.85% time saving of affine motion estimation with a 0.16% Bjøontegaard delta bitrate (BDBR) increase.
12
Jiang, Xiantao, Mo Xiang, Jiayuan Jin, and Tian Song. "Extreme Learning Machine-Enabled Coding Unit Partitioning Algorithm for Versatile Video Coding." Information 14, no. 9 (September 7, 2023): 494. http://dx.doi.org/10.3390/info14090494.
Abstract:
The versatile video coding (VVC) standard offers improved coding efficiency compared to the high efficiency video coding (HEVC) standard in multimedia signal coding. However, this increased efficiency comes at the cost of increased coding complexity. This work proposes an efficient coding unit partitioning algorithm based on an extreme learning machine (ELM), which can reduce the coding complexity while ensuring coding efficiency. Firstly, the coding unit size decision is modeled as a classification problem. Secondly, an ELM classifier is trained to predict the coding unit size. In the experiment, the proposed approach is verified based on the VVC reference model. The results show that the proposed method can reduce coding complexity significantly, and good image quality can be obtained.
13
Lee, Taesik, and Dongsan Jun. "Fast Mode Decision Method of Multiple Weighted Bi-Predictions Using Lightweight Multilayer Perceptron in Versatile Video Coding." Electronics 12, no. 12 (June 15, 2023): 2685. http://dx.doi.org/10.3390/electronics12122685.
Abstract:
Versatile Video Coding (VVC), the state-of-the-art video coding standard, was developed by the Joint Video Experts Team (JVET) of ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG) in 2020. Although VVC can provide powerful coding performance, it requires tremendous computational complexity to determine the optimal mode decision during the encoding process. In particular, VVC adopted the bi-prediction with CU-level weight (BCW) as one of the new tools, which enhanced the coding efficiency of conventional bi-prediction by assigning different weights to the two prediction blocks in the process of inter prediction. In this study, we investigate the statistical characteristics of input features that exhibit a correlation with the BCW and define four useful types of categories to facilitate the inter prediction of VVC. With the investigated input features, a lightweight neural network with multilayer perceptron (MLP) architecture is designed to provide high accuracy and low complexity. We propose a fast BCW mode decision method with a lightweight MLP to reduce the computational complexity of the weighted multiple bi-prediction in the VVC encoder. The experimental results show that the proposed method significantly reduced the BCW encoding complexity by up to 33% with unnoticeable coding loss, compared to the VVC test model (VTM) under the random-access (RA) configuration.
14
Teng, Guowei, Danqi Xiong, Ran Ma, and Ping An. "Decision tree accelerated CTU partition algorithm for intra prediction in versatile video coding." PLOS ONE 16, no. 11 (November 8, 2021): e0258890. http://dx.doi.org/10.1371/journal.pone.0258890.
Abstract:
Versatile video coding (VVC) achieves enormous improvement over the advanced high efficiency video coding (HEVC) standard due to the adoption of the quadtree with nested multi-type tree (QTMT) partition structure and other coding tools. However, the computational complexity increases dramatically as well. To tackle this problem, we propose a decision tree accelerated coding tree units (CTU) partition algorithm for intra prediction in VVC. Firstly, specially designated image features are extracted to characterize the coding unit (CU) complexity. Then, the trained decision tree is employed to predict the partition results. Finally, based on our newly designed intra prediction framework, the partition process is early terminated or redundant partition modes are screened out. The experimental results show that the proposed algorithm could achieve around 52% encoding time reduction for various test video sequences on average with only 1.75% Bjontegaard delta bit rate increase compared with the reference test model VTM9.0 of VVC.
15
Palau, Roberta De Carvalho Nobre, Bianca Santos da Cunha Silveira, Robson André Domanski, Marta Breunig Loose, Arthur Alves Cerveira, Felipe Martin Sampaio, Daniel Palomino, Marcelo Schiavon Porto, Guilherme Ribeiro Corrêa, and Luciano Volcan Agostini. "Modern Video Coding: Methods, Challenges and Systems." Journal of Integrated Circuits and Systems 16, no. 2 (August 16, 2021): 1–12. http://dx.doi.org/10.29292/jics.v16i2.503.
Abstract:
With the increasing demand for digital video applications in our daily lives, video coding and decoding become critical tasks that must be supported by several types of devices and systems. This paper presents a discussion of the main challenges to design dedicated hardware architectures based on modern hybrid video coding formats, such as the High Efficiency Video Coding (HEVC), the AOMedia Video 1 (AV1) and the Versatile Video Coding (VVC). The paper discusses eachstep of the hybrid video coding process, highlighting the main challenges for each codec and discussing the main hardware solutions published in the literature. The discussions presented in the paper show that there are still many challenges to be overcome and open research opportunities, especially for the AV1 and VVC codecs. Most of these challenges are related to the high throughput required for processing high and ultrahigh resolution videos in real time and to energy constraints of multimedia-capable devices.
16
Song, Hyeonju, and Yung-Lyul Lee. "Inverse Transform Using Linearity for Video Coding." Electronics 11, no. 5 (March 1, 2022): 760. http://dx.doi.org/10.3390/electronics11050760.
Abstract:
In hybrid block-based video coding, transform plays an important role in energy compaction. Transform coding converts residual data in the spatial domain into frequency domain data, thereby concentrating energy in a lower frequency band. In VVC (versatile video coding), the primary transform is performed using DCT-II (discrete cosine transform type 2), DST-VII (discrete sine transform type 7), and DCT-VIII (discrete cosine transform type 8). Considering that DCT-II, DST-VII, and DCT-VIII are all linear transforms, inverse transform is proposed to reduce the number of computations by using the linearity of transform. When the proposed inverse transform using linearity is applied to the VVC encoder and decoder, run-time savings can be achieved without decreasing the coding performance relative to the VVC decoder. It is shown that, under VVC common-test conditions (CTC), average decoding time savings values of 4% and 10% are achieved for all intra (AI) and random access (RA) configurations, respectively.
17
Shu, Zhengjie, Junyi Li, Zongju Peng, Fen Chen, and Mei Yu. "Intra Complexity Control Algorithm for VVC." Electronics 11, no. 16 (August 17, 2022): 2572. http://dx.doi.org/10.3390/electronics11162572.
Abstract:
Versatile Video Coding (VVC) has advantages over High Efficiency Video Coding (HEVC); it can save nearly half of the bit rate and significantly improve the compression efficiency, but VVC’s coding complexity is extremely high. Therefore, VVC encoders are difficult to implement in video devices with different computing capabilities and power constraints. In this paper, we apply texture information and propose a VVC intra complexity control algorithm. The algorithm assigns a different encoding time to each CU based on the corresponding texture entropy. Besides, the complexity reduction strategy at the CU level is designed to balance the complexity control while taking rate-distortion performance into consideration. Experiments in our paper show that the coding complexity can be accurately controlled from 90% to 70% with a slight loss of RD performance.
18
JABALLAH, Sami, and Mohamed-Chaker LARABI. "Complexity Optimization for the Upcoming Versatile Video Coding Standard." Electronic Imaging 2020, no. 9 (January 26, 2020): 286–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.9.iqsp-286.
Abstract:
The Versatile Video Coding (VVC) is forseen as the next generation video coding standard. The main objective is to achieve coding efficiency improvement of about 50% bit-rate reduction compared to the previous standard HEVC at the same visual quality by 2020. In this paper, a fast VVC encoder is proposed based on an early split termination for fast intra CU selection. Taking into account edge complexity of the block and the best intra prediction mode obtained at the current block size, an early split termination is proposed. Using spatial neighboring coding unit depths (quad-tree, binary-tree and ternary-tree depths), the depth probability measure is computed and used to define the stopping criterion. The proposed algorithm is evaluated on nine commoly used test video sequences. Compared to the current VTM3.0 in all intra high efficiency and LowDelayP configuration cases, the proposed algorithm outperforms the anchor scheme in terms of encoding time with a slightly degradation in coding efficiency.
19
Lee, Sujin, Sang-hyo Park, and Dongsan Jun. "Object-Cooperated Ternary Tree Partitioning Decision Method for Versatile Video Coding." Sensors 22, no. 17 (August 23, 2022): 6328. http://dx.doi.org/10.3390/s22176328.
Abstract:
In this paper, we propose an object-cooperated decision method for efficient ternary tree (TT) partitioning that reduces the encoding complexity of versatile video coding (VVC). In most previous studies, the VVC complexity was reduced using decision schemes based on the encoding context, which do not apply object detecion models. We assume that high-level objects are important for deciding whether complex TT partitioning is required because they can provide hints on the characteristics of a video. Herein, we apply an object detection model that discovers and extracts the high-level object features—the number and ratio of objects from frames in a video sequence. Using the extracted features, we propose machine learning (ML)-based classifiers for each TT-split direction to efficiently reduce the encoding complexity of VVC and decide whether the TT-split process can be skipped in the vertical or horizontal direction. The TT-split decision of classifiers is formulated as a binary classification problem. Experimental results show that the proposed method more effectively decreases the encoding complexity of VVC than a state-of-the-art model based on ML.
20
Zhao, Shuai, Xiwu Shang, Guozhong Wang, and Haiwu Zhao. "A Fast Algorithm for Intra-Frame Versatile Video Coding Based on Edge Features." Sensors 23, no. 13 (July 7, 2023): 6244. http://dx.doi.org/10.3390/s23136244.
Abstract:
Versatile Video Coding (VVC) introduces many new coding technologies, such as quadtree with nested multi-type tree (QTMT), which greatly improves the efficiency of VVC coding. However, its computational complexity is higher, which affects the application of VVC in real-time scenarios. Aiming to solve the problem of the high complexity of VVC intra coding, we propose a low-complexity partition algorithm based on edge features. Firstly, the Laplacian of Gaussian (LOG) operator was used to extract the edges in the coding frame, and the edges were divided into vertical and horizontal edges. Then, the coding unit (CU) was equally divided into four sub-blocks in the horizontal and vertical directions to calculate the feature values of the horizontal and vertical edges, respectively. Based on the feature values, we skipped unnecessary partition patterns in advance. Finally, for the CUs without edges, we decided to terminate the partition process according to the depth information of neighboring CUs. The experimental results show that compared with VTM-13.0, the proposed algorithm can save 54.08% of the encoding time on average, and the BDBR (Bjøntegaard delta bit rate) only increases by 1.61%.
21
Yoon, Yong-Uk, and Jae-Gon Kim. "Activity-Based Block Partitioning Decision Method for Versatile Video Coding." Electronics 11, no. 7 (March 28, 2022): 1061. http://dx.doi.org/10.3390/electronics11071061.
Abstract:
Versatile Video Coding (VVC), the latest international video coding standard, has more than twice the compression performance of High-Efficiency Video Coding (HEVC) through adopting various coding techniques. The multi-type tree (MTT) block structure offers more advanced flexible block partitioning by allowing the binary tree (BT) and ternary tree (TT) structures, as well as the quadtree (QT) structure. Because VVC selects the optimal block partition by performing encoding on all possible CU partitions, the encoding complexity increases enormously. In this paper, we observe the relationship between block partitions and activity that indicates block texture complexity. Based on experimental observations, we propose an activity-based fast block partitioning decision method to reduce the encoding complexity. The proposed method uses only information of the current block without using the information of neighboring or upper blocks, and also minimizes the dependency on QP. For these reasons, the proposed algorithm is simple and parallelizable. In addition, by utilizing the gradient calculation used in VVC’s ALF, a VVC-friendly fast algorithm was designed. The proposed method consists of two-step decision-making processes. The first step terminates the block partitioning early based on observed posterior probability through the relationship between the block size and activity per sample. Next, the sub-activities of the current block are used to determine the type and direction of partitioning. The experimental results show that in the all-intra configuration, the proposed method can reduce the encoding time of the VVC test model (VTM) by up to 45.15% with 2.80% BD-rate loss.
22
Lee, Junghyun, and Jechang Jeong. "Performance Comparison of Weak Filtering in HEVC and VVC." Electronics 9, no. 6 (June 9, 2020): 960. http://dx.doi.org/10.3390/electronics9060960.
Abstract:
This study describes the need to improve the weak filtering method for the in-loop filter process used identically in versatile video coding (VVC) and high efficiency video coding (HEVC). The weak filtering process used by VVC has been adopted and maintained since Draft Four during H.265/advanced video coding (AVC) standardization. Because the encoding process in the video codec utilizes block structural units, deblocking filters are essential. However, as many of the deblocking filters require a complex calculation process, it is necessary to ensure that they have a reasonable effect. This study evaluated the performance of the weak filtering portion of the VVC and confirmed that it is not functioning effectively, unlike its performance in the HEVC. The method of excluding the whole of weak filtering from VVC, which is a non-weak filtering method, should be considered in VVC standardization. In experimental result in this study, the non-weak filtering method brings 0.40 Y-Bjontegaard-Delta Bit-Rate (BDBR) gain over VVC Test Model (VTM) 6.0.
23
Li, Wei, Xiantao Jiang, Jiayuan Jin, Tian Song, and Fei Richard Yu. "Saliency-Enabled Coding Unit Partitioning and Quantization Control for Versatile Video Coding." Information 13, no. 8 (August 19, 2022): 394. http://dx.doi.org/10.3390/info13080394.
Abstract:
The latest video coding standard, versatile video coding (VVC), has greatly improved coding efficiency over its predecessor standard high efficiency video coding (HEVC), but at the expense of sharply increased complexity. In the context of perceptual video coding (PVC), the visual saliency model that utilizes the characteristics of the human visual system to improve coding efficiency has become a reliable method due to advances in computer performance and visual algorithms. In this paper, a novel VVC optimization scheme compliant PVC framework is proposed, which consists of fast coding unit (CU) partition algorithm and quantization control algorithm. Firstly, based on the visual saliency model, we proposed a fast CU division scheme, including the redetermination of the CU division depth by calculating Scharr operator and variance, as well as the executive decision for intra sub-partitions (ISP), to reduce the coding complexity. Secondly, a quantization control algorithm is proposed by adjusting the quantization parameter based on multi-level classification of saliency values at the CU level to reduce the bitrate. In comparison with the reference model, experimental results indicate that the proposed method can reduce about 47.19% computational complexity and achieve a bitrate saving of 3.68% on average. Meanwhile, the proposed algorithm has reasonable peak signal-to-noise ratio losses and nearly the same subjective perceptual quality.
24
Kim, Seonjae, Dongsan Jun, Byung-Gyu Kim, Seungkwon Beack, Misuk Lee, and Taejin Lee. "Two-Dimensional Audio Compression Method Using Video Coding Schemes." Electronics 10, no. 9 (May 6, 2021): 1094. http://dx.doi.org/10.3390/electronics10091094.
Abstract:
As video compression is one of the core technologies that enables seamless media streaming within the available network bandwidth, it is crucial to employ media codecs to support powerful coding performance and higher visual quality. Versatile Video Coding (VVC) is the latest video coding standard developed by the Joint Video Experts Team (JVET) that can compress original data hundreds of times in the image or video; the latest audio coding standard, Unified Speech and Audio Coding (USAC), achieves a compression rate of about 20 times for audio or speech data. In this paper, we propose a pre-processing method to generate a two-dimensional (2D) audio signal as an input of a VVC encoder, and investigate the applicability to 2D audio compression using the video coding scheme. To evaluate the coding performance, we measure both signal-to-noise ratio (SNR) and bits per sample (bps). The experimental result shows the possibility of researching 2D audio encoding using video coding schemes.
25
Park, Dohyeon, Gihwa Moon, Byung Tae Oh, and Jae-Gon Kim. "Coarse-to-Fine Network-Based Intra Prediction in Versatile Video Coding." Sensors 23, no. 23 (November 27, 2023): 9452. http://dx.doi.org/10.3390/s23239452.
Abstract:
After the development of the Versatile Video Coding (VVC) standard, research on neural network-based video coding technologies continues as a potential approach for future video coding standards. Particularly, neural network-based intra prediction is receiving attention as a solution to mitigate the limitations of traditional intra prediction performance in intricate images with limited spatial redundancy. This study presents an intra prediction method based on coarse-to-fine networks that employ both convolutional neural networks and fully connected layers to enhance VVC intra prediction performance. The coarse networks are designed to adjust the influence on prediction performance depending on the positions and conditions of reference samples. Moreover, the fine networks generate refined prediction samples by considering continuity with adjacent reference samples and facilitate prediction through upscaling at a block size unsupported by the coarse networks. The proposed networks are integrated into the VVC test model (VTM) as an additional intra prediction mode to evaluate the coding performance. The experimental results show that our coarse-to-fine network architecture provides an average gain of 1.31% Bjøntegaard delta-rate (BD-rate) saving for the luma component compared with VTM 11.0 and an average of 0.47% BD-rate saving compared with the previous related work.
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Bouaafia, Soulef, Seifeddine Messaoud, Randa Khemiri, and Fatma Elzahra Sayadi. "VVC In-Loop Filtering Based on Deep Convolutional Neural Network." Computational Intelligence and Neuroscience 2021 (July 7, 2021): 1–9. http://dx.doi.org/10.1155/2021/9912839.
Abstract:
With the rapid advancement in many multimedia applications, such as video gaming, computer vision applications, and video streaming and surveillance, video quality remains an open challenge. Despite the existence of the standardized video quality as well as high definition (HD) and ultrahigh definition (UHD), enhancing the quality for the video compression standard will improve the video streaming resolution and satisfy end user’s quality of service (QoS). Versatile video coding (VVC) is the latest video coding standard that achieves significant coding efficiency. VVC will help spread high-quality video services and emerging applications, such as high dynamic range (HDR), high frame rate (HFR), and omnidirectional 360-degree multimedia compared to its predecessor high efficiency video coding (HEVC). Given its valuable results, the emerging field of deep learning is attracting the attention of scientists and prompts them to solve many contributions. In this study, we investigate the deep learning efficiency to the new VVC standard in order to improve video quality. However, in this work, we propose a wide-activated squeeze-and-excitation deep convolutional neural network (WSE-DCNN) technique-based video quality enhancement for VVC. Thus, the VVC conventional in-loop filtering will be replaced by the suggested WSE-DCNN technique that is expected to eliminate the compression artifacts in order to improve visual quality. Numerical results demonstrate the efficacy of the proposed model achieving approximately − 2.85 % , − 8.89 % , and − 10.05 % BD-rate reduction of the luma (Y) and both chroma (U, V) components, respectively, under random access profile.
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Citadin, Nicole, Ismael Seidel, Mateus Grellert, and José Luis Güntzel. "Variable Block Size Fractional Motion Estimation Hardware Architecture for VVC and HEVC Standards." Journal of Integrated Circuits and Systems 18, no. 3 (December 28, 2023): 1–12. http://dx.doi.org/10.29292/jics.v18i3.787.
Abstract:
The ever-increasing growth in digital video consumption motivates the research and development of new video coding standards to improve coding efficiency. Among the several new tools that the Versatile Video Coding (VVC) standard introduced lies the Quadtree Plus Multi-Type Tree (QT+MTT), which improves upon the quadtree of High Efficiency Video Coding (HEVC) in terms of coding efficiency. Nevertheless, such improvements come at the cost of increased complexity. Hence, to meet the real-time and energy efficiency requirements, embedded devices must adopt techniques to effectively reduce the VVC complexity, including customized hardware accelerators. This work presents a low-energy hardware architecture design for the Fractional Motion Estimation (FME), one of the most critical steps of HEVC and VVC encoders. The proposed architecture supports the Switchable Interpolation Filter (SIF) of VVC and was synthesized to enable Variable Block Size (VBS) from 8×8 up to 128×128 sized blocks so that it can perform the FME of most partitions of the QT+MTT from VVC. The results show increases of at most 4.52% in area and 10.79% in total power for the extra hardware needed to support VBS, and up to 9.15% and 15.72%, in area and power, respectively, for supporting up to 128×128 block sizes.
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Panagou, Natalia, Panagiotis Belememis, and Maria Koziri. "Image Segmentation Methods for Subpicture Partitioning in the VVC Video Encoder." Electronics 11, no. 13 (July 1, 2022): 2070. http://dx.doi.org/10.3390/electronics11132070.
Abstract:
The emergence of the new generation video coding standard, Versatile Video Coding (VVC), has brought along novel features rendering the new standard more efficient and flexible than its predecessors. Aside from efficient compression of 8 k or higher camera-captured content, VVC also supports a wide range of applications, including computer-generated content, high dynamic range (HDR) content, multilayer and multi-view coding, video region extraction, as well as 360° video. One of the newly introduced coding tools in VVC, offering extraction and independent coding of rectangular sub-areas within a frame, is called Subpicture. In this work, we turn our attention to frame partitioning using Subpictures in VVC, and more particularly, a content-aware partitioning is considered. To achieve that, we make use of image segmentation algorithms and properly modify them to operate on a per Coding Tree Unit (CTU) basis in order to render them compliant with the standard’s restrictions. Additionally, since subpicture boundaries need to comply with slice boundaries, we propose two methods for properly partitioning a frame using tiles/slices aiming to avoid over-partitioning of a frame. The proposed algorithms are evaluated regarding both compression efficiency and image segmentation effectiveness. Our evaluation results indicate that the proposed partitioning schemes have a negligible impact on compression efficiency and video quality
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Biatek, Thibaud, Mohsen Abdoli, Mickael Raulet, Adam Wieckowski, Christian Lehman, Benjamin Bross, Philippe De Lagrange, Edouard François, Ralf Schaefer, and Jean Lefeuvre. "Versatile Video Coding for 3.0 Next Generation Digital TV in Brazil." SET INTERNATIONAL JOURNAL OF BROADCAST ENGINEERING 2021, no. 1 (December 1, 2021): 9–17. http://dx.doi.org/10.18580/setijbe.2021.1.
Abstract:
In the past few decades, the video broadcast ecosystem has gone through major changes; Originally transmitted using analog signals, it has been more and more transitioned toward digital, leveraging compression technologies and transport protocols, principally developed by MPEG. Along this way, the introduction of new video formats was achieved with standardization of new compression technologies for their better bandwidth preservation. Notably, SD with MPEG-2, HD with H.264, 4K/UHD with HEVC. In Brazil, the successive generations of digital broadcasting systems were developed by the SBTVD Forum, from TV-1.0 to TV-3.0 nowadays. The ambition of TV-3.0 is significantly higher than that of previous generations as it targets the delivery of IPbased signals for applications, such as 8K, HDR, virtual and augmented reality. To deliver such services, compressed video signals shall fit into a limited bandwidth, requiring even more advanced compression technologies. The Versatile Video Coding standard (H.266/VVC), has been finalized by the JVET committee in 2021 and is a relevant candidate to address the TV3.0 requirements. VVC is versatile by nature thanks to its dedicated tools for efficient compression of various formats, from 8K to 360°, and provides around 50% of bitrate saving compared to its predecessor HEVC. This paper presents the VVC-based compression system that has been proposed to the SBTVD call for proposals for TV-3.0. A technical description of VVC and an evaluation of its coding performance is provided. In addition, an end-to-end live transmission chain is demonstrated, supporting 4K real-time encoding and decoding with a low glass-to-glass latency.
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He, Liqiang, Shuhua Xiong, Ruolan Yang, Xiaohai He, and Honggang Chen. "Low-Complexity Multiple Transform Selection Combining Multi-Type Tree Partition Algorithm for Versatile Video Coding." Sensors 22, no. 15 (July 25, 2022): 5523. http://dx.doi.org/10.3390/s22155523.
Abstract:
Despite the fact that Versatile Video Coding (VVC) achieves a superior coding performance to High-Efficiency Video Coding (HEVC), it takes a lot of time to encode video sequences due to the high computational complexity of the tools. Among these tools, Multiple Transform Selection (MTS) require the best of several transforms to be obtained using the Rate-Distortion Optimization (RDO) process, which increases the time spent video encoding, meaning that VVC is not suited to real-time sensor application networks. In this paper, a low-complexity multiple transform selection, combined with the multi-type tree partition algorithm, is proposed to address the above issue. First, to skip the MTS process, we introduce a method to estimate the Rate-Distortion (RD) cost of the last Coding Unit (CU) based on the relationship between the RD costs of transform candidates and the correlation between Sub-Coding Units’ (sub-CUs’) information entropy under binary splitting. When the sum of the RD costs of sub-CUs is greater than or equal to their parent CU, the RD checking of MTS will be skipped. Second, we make full use of the coding information of neighboring CUs to terminate MTS early. The experimental results show that, compared with the VVC, the proposed method achieves a 26.40% reduction in time, with a 0.13% increase in Bjøontegaard Delta Bitrate (BDBR).
31
Zhao, Jinchao, Aobo Wu, and Qiuwen Zhang. "SVM-Based Fast CU Partition Decision Algorithm for VVC Intra Coding." Electronics 11, no. 14 (July 8, 2022): 2147. http://dx.doi.org/10.3390/electronics11142147.
Abstract:
As a new coding standard, Versatile Video Coding (VVC) introduces the quad-tree plus multi-type tree (QTMT) partition structure, which significantly improves coding efficiency compared to High-Efficiency Video Coding (HEVC). The QTMT partition structure further enhances the flexibility of coding unit (CU) partitioning and improves the efficiency of VVC encoding high-resolution video, but introduces an unacceptable coding complexity at the same time. This paper proposes an SVM-based fast CU partition decision algorithm to reduce the coding complexity for VVC. First, the proportion of split modes with different CU sizes is analyzed to explore a method to effectively reduce coding complexity. Then, more reliable correlation features are selected based on the maximum ratio of the standard deviation (SD) and the edge point ratio (EPR) in sub-CUs. Finally, two SVM models are designed and trained using the selected features to provide guidance for deciding whether to divide and the direction of partition. The simulation results indicate that the proposed algorithm can save 54.05% coding time on average with 1.54% BDBR increase compared with VTM7.0.
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Taabane, Ibrahim, Daniel Menard, Anass Mansouri, and Ali Ahaitouf. "Machine Learning Based Fast QTMTT Partitioning Strategy for VVenC Encoder in Intra Coding." Electronics 12, no. 6 (March 11, 2023): 1338. http://dx.doi.org/10.3390/electronics12061338.
Abstract:
The newest video compression standard, Versatile Video Coding (VVC), was finalized in July 2020 by the Joint Video Experts Team (JVET). Its main goal is to reduce the bitrate by 50% over its predecessor video coding standard, the High Efficiency Video Coding (HEVC). Due to the new advanced tools and features included in VVC, it actually provides high coding performances—for instance, the Quad Tree with nested Multi-Type Tree (QTMTT) involved in the partitioning block. Furthermore, VVC introduces various techniques that allow for superior performance compared to HEVC, but with an increase in the computational complexity. To tackle this complexity, a fast Coding Unit partition algorithm based on machine learning for the intra configuration in VVC is proposed in this work. The proposed algorithm is formed by five binary Light Gradient Boosting Machine (LightGBM) classifiers, which can directly predict the most probable split mode for each coding unit without passing through the exhaustive process known as Rate Distortion Optimization (RDO). These LightGBM classifiers were offline trained on a large dataset; then, they were embedded on the optimized implementation of VVC known as VVenC. The results of our experiment show that our proposed approach has good trade-offs in terms of time-saving and coding efficiency. Depending on the preset chosen, our approach achieves an average time savings of 30.21% to 82.46% compared to the VVenC encoder anchor, and a Bjøntegaard Delta Bitrate (BDBR) increase of 0.67% to 3.01%, respectively.
33
Cho, Seunghyun, Dong-Wook Kim, and Seung-Won Jung. "Quality enhancement of VVC intra-frame coding for multimedia services over the Internet." International Journal of Distributed Sensor Networks 16, no. 5 (May 2020): 155014772091764. http://dx.doi.org/10.1177/1550147720917647.
Abstract:
In this article, versatile video coding, the next-generation video coding standard, is combined with a deep convolutional neural network to achieve state-of-the-art image compression efficiency. The proposed hierarchical grouped residual dense network exhaustively exploits hierarchical features in each architectural level to maximize the image quality enhancement capability. The basic building block employed for hierarchical grouped residual dense network is residual dense block which exploits hierarchical features from internal convolutional layers. Residual dense blocks are then combined into a grouped residual dense block exploiting hierarchical features from residual dense blocks. Finally, grouped residual dense blocks are connected to comprise a hierarchical grouped residual dense block so that hierarchical features from grouped residual dense blocks can also be exploited for quality enhancement of versatile video coding intra-coded images. Various non-architectural and architectural aspects affecting the training efficiency and performance of hierarchical grouped residual dense network are explored. The proposed hierarchical grouped residual dense network respectively obtained 10.72% and 14.3% of Bjøntegaard-delta-rate gains against versatile video coding in the experiments conducted on two public image datasets with different characteristics to verify the image compression efficiency.
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Park, Sang-Hyo, and Je-Won Kang. "Fast Affine Motion Estimation for Versatile Video Coding (VVC) Encoding." IEEE Access 7 (2019): 158075–84. http://dx.doi.org/10.1109/access.2019.2950388.
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Garcia, Bruna, Bianca Silveira, Claudio Diniz, Daniel Palomino, and Guilherme Correa. "Low-Power Inverse Multiple Transform Hardware Design for 8K@60fps Real-Time VVC Decoding." Journal of Integrated Circuits and Systems 18, no. 3 (December 28, 2023): 1–8. http://dx.doi.org/10.29292/jics.v18i3.799.
Abstract:
The Versatile Video Coding (VVC) is a new standard released in 2020 and is considered the state-of-the-art technology in video coding. It introduces several innovative tools to achieve high coding efficiency, but, on the other side, requires a significantly higher computational effort. One of the innovations of the standard is the Multiple Transform Selection (MTS), which plays a crucial role in improving coding efficiency. MTS supports square and rectangular transform blocks and includes three transform types (DCT-II, DCT-VIII, and DST-VII) that can be combined in horizontal and vertical directions. As a result, VVC codecs must support a wide range of transform types and formats, making the development of hardware solutions essential to enable real-time processing. This work presents a dedicated hardware architecture for all inverse transforms in the VVC decoder. The proposed architecture performs one-dimensional transforms for all sizes supported in the VVC standard, allowing for the combination into 2D square and rectangular transforms, ranging from 4×4 to 64×64 blocks for IDCT-II and from 4×4 to 32×32 for IDCT-VIII and IDST-VII. The proposed architecture can process videos of up to UHD 8K@60fps resolution in real time, with a power consumption of 778 mW.
36
Tsai, Yu-Hsiang, Chen-Rung Lu, Mei-Juan Chen, Meng-Chun Hsieh, Chieh-Ming Yang, and Chia-Hung Yeh. "Visual Perception Based Intra Coding Algorithm for H.266/VVC." Electronics 12, no. 9 (May 1, 2023): 2079. http://dx.doi.org/10.3390/electronics12092079.
Abstract:
The latest international video coding standard, H.266/Versatile Video Coding (VVC), supports high-definition videos, with resolutions from 4 K to 8 K or even larger. It offers a higher compression ratio than its predecessor, H.265/High Efficiency Video Coding (HEVC). In addition to the quadtree partition structure of H.265/HEVC, the nested multi-type tree (MTT) structure of H.266/VVC provides more diverse splits through binary and ternary trees. It also includes many new coding tools, which tremendously increases the encoding complexity. This paper proposes a fast intra coding algorithm for H.266/VVC based on visual perception analysis. The algorithm applies the factor of average background luminance for just-noticeable-distortion to identify the visually distinguishable (VD) pixels within a coding unit (CU). We propose calculating the variances of the numbers of VD pixels in various MTT splits of a CU. Intra sub-partitions and matrix weighted intra prediction are turned off conditionally based on the variance of the four variances for MTT splits and a thresholding criterion. The fast horizontal/vertical splitting decisions for binary and ternary trees are proposed by utilizing random forest classifiers of machine learning techniques, which use the information of VD pixels and the quantization parameter. Experimental results show that the proposed algorithm achieves around 47.26% encoding time reduction with a Bjøntegaard Delta Bitrate (BDBR) of 1.535% on average under the All Intra configuration. Overall, this algorithm can significantly speed up H.266/VVC intra coding and outperform previous studies.
37
Jing, Zhiyong, Wendi Zhu, and Qiuwen Zhang. "A Fast VVC Intra Prediction Based on Gradient Analysis and Multi-Feature Fusion CNN." Electronics 12, no. 9 (April 23, 2023): 1963. http://dx.doi.org/10.3390/electronics12091963.
Abstract:
The Joint Video Exploration Team (JVET) has created the Versatile Video Coding Standard (VVC/H.266), the most up-to-date video coding standard, offering a broad selection of coding tools. The maturity of commercial VVC codecs can significantly reduce costs and improve coding efficiency. However, the latest video coding standards have introduced binomial and trinomial tree partitioning methods, which cause the coding units (CUs) to have various shapes, increasing the complexity of coding. This article proposes a technique to simplify VVC intra prediction through the use of gradient analysis and a multi-feature fusion CNN. The gradient of CUs is computed by employing the Sobel operator, the calculation results are used for predecision-making. Further decisions can be made by CNN for coding units that cannot be judged whether they should be segmented or not. We calculate the standard deviation (SD) and the initial depth as the input features of the CNN. To implement this method, the initial depth can be determined by constructing a segmented depth prediction dictionary. For the initial segmentation depth of the coding unit, regardless of its shape, it can also be determined by consulting the dictionary. The algorithm can determine whether to split CUs of varying sizes, decreasing the complexity of the CU division process and making VVC more practical. Experimental results demonstrate that the proposed algorithm can reduce encoding time by 36.56% with a minimal increase of 1.06% Bjøntegaard delta bit rate (BD-BR) compared to the original algorithm.
38
Schiopu, Ionut, and Adrian Munteanu. "Deep Learning Post-Filtering Using Multi-Head Attention and Multiresolution Feature Fusion for Image and Intra-Video Quality Enhancement." Sensors 22, no. 4 (February 10, 2022): 1353. http://dx.doi.org/10.3390/s22041353.
Abstract:
The paper proposes a novel post-filtering method based on convolutional neural networks (CNNs) for quality enhancement of RGB/grayscale images and video sequences. The lossy images are encoded using common image codecs, such as JPEG and JPEG2000. The video sequences are encoded using previous and ongoing video coding standards, high-efficiency video coding (HEVC) and versatile video coding (VVC), respectively. A novel deep neural network architecture is proposed to estimate fine refinement details for full-, half-, and quarter-patch resolutions. The proposed architecture is built using a set of efficient processing blocks designed based on the following concepts: (i) the multi-head attention mechanism for refining the feature maps, (ii) the weight sharing concept for reducing the network complexity, and (iii) novel block designs of layer structures for multiresolution feature fusion. The proposed method provides substantial performance improvements compared with both common image codecs and video coding standards. Experimental results on high-resolution images and standard video sequences show that the proposed post-filtering method provides average BD-rate savings of 31.44% over JPEG and 54.61% over HEVC (x265) for RGB images, Y-BD-rate savings of 26.21% over JPEG and 15.28% over VVC (VTM) for grayscale images, and 15.47% over HEVC and 14.66% over VVC for video sequences.
39
Li, Yue, Fei Luo, and Yapei Zhu. "Temporal Prediction Model-Based Fast Inter CU Partition for Versatile Video Coding." Sensors 22, no. 20 (October 12, 2022): 7741. http://dx.doi.org/10.3390/s22207741.
Abstract:
Versatile video coding (VVC) adopts an advanced quad-tree plus multi-type tree (QTMT) coding structure to obtain higher compression efficiency, but it comes at the cost of a considerable increase in coding complexity. To effectively reduce the coding complexity of the QTMT-based coding unit (CU) partition, we propose a fast inter CU partition method based on a temporal prediction model, which includes early termination QTMT partition and early skipping multi-type tree (MT) partition. Firstly, according to the position of the current CU, we extract the optimal CU partition information of the position corresponding to the previously coded frames. We then establish a temporal prediction model based on temporal CU partition information to predict the current CU partition. Finally, to reduce the cumulative of errors of the temporal prediction model, we further extract the motion vector difference (MVD) of the CU to determine whether the QTMT partition can be terminated early. The experimental results show that the proposed method can reduce the inter coding complexity of VVC by 23.19% on average, while the Bjontegaard delta bit rate (BDBR) is only increased by 0.97% on average under the Random Access (RA) configuration.
40
Lee, Minhun, HyeonJu Song, Jeeyoon Park, Byeungwoo Jeon, Jungwon Kang, Jae-Gon Kim, Yung-Lyul Lee, Je-Won Kang, and Donggyu Sim. "Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis." IEIE Transactions on Smart Processing & Computing 12, no. 2 (April 30, 2023): 122–54. http://dx.doi.org/10.5573/ieiespc.2023.12.2.122.
41
Ren, Weizheng, Wei He, and Yansong Cui. "An Improved Fast Affine Motion Estimation Based on Edge Detection Algorithm for VVC." Symmetry 12, no. 7 (July 8, 2020): 1143. http://dx.doi.org/10.3390/sym12071143.
Abstract:
As a newly proposed video coding standard, Versatile Video Coding (VVC) has adopted some revolutionary techniques compared to High Efficiency Video Coding (HEVC). The multiple-mode affine motion compensation (MM-AMC) adopted by VVC saves approximately 15%-25% Bjøntegaard Delta Bitrate (BD-BR), with an inevitable increase of encoding time. This paper gives an overview of both the 4-parameter affine motion model and the 6-parameter affine motion model, analyzes their performances, and proposes improved algorithms according to the symmetry of iterative gradient descent for fast affine motion estimation. Finally, the proposed algorithms and symmetric MM-AMC flame of VTM-7.0 are compared. The results show that the proposed algorithms save 6.65% total encoding time on average, which saves approximately 30% encoding time of affine motion compensation.
42
Wang, Yanjun, Yong Liu, Jinchao Zhao, and Qiuwen Zhang. "Low-Complexity Fast CU Classification Decision Method Based on LGBM Classifier." Electronics 12, no. 11 (May 31, 2023): 2488. http://dx.doi.org/10.3390/electronics12112488.
Abstract:
At present, the latest video coding standard is Versatile Video Coding (VVC). Although the coding efficiency of VVC is significantly improved compared to the previous generation, standard High-Efficiency Video Coding (HEVC), it also leads to a sharp increase in coding complexity. VVC significantly improves HEVC by adopting the quadtree with nested multi-type tree (QTMT) partition structure, which has been proven to be very effective. This paper proposes a low-complexity fast coding unit (CU) partition decision method based on the light gradient boosting machine (LGBM) classifier. Representative features were extracted to train a classifier matching the framework. Secondly, a new fast CU decision framework was designed for the new features of VVC, which could predict in advance whether the CU was divided, whether it was divided by quadtree (QT), and whether it was divided horizontally or vertically. To solve the multi-classification problem, the technique of creating multiple binary classification problems was used. Subsequently, a multi-threshold decision-making scheme consisting of four threshold points was proposed, which achieved a good balance between time savings and coding efficiency. According to the experimental results, our method achieved a significant reduction in encoding time, ranging from 47.93% to 54.27%, but only improved the Bjøntegaard delta bit-rate (BDBR) by 1.07%~1.57%. Our method showed good performance in terms of both encoding time reduction and efficiency.
43
Martínez-Rach, Miguel O., Héctor Migallón, Otoniel López-Granado, Vicente Galiano, and Manuel P. Malumbres. "Performance Overview of the Latest Video Coding Proposals: HEVC, JEM and VVC." Journal of Imaging 7, no. 2 (February 22, 2021): 39. http://dx.doi.org/10.3390/jimaging7020039.
Abstract:
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.
44
Bross, Benjamin, Jianle Chen, Jens-Rainer Ohm, Gary J. Sullivan, and Ye-Kui Wang. "Developments in International Video Coding Standardization After AVC, With an Overview of Versatile Video Coding (VVC)." Proceedings of the IEEE 109, no. 9 (September 2021): 1463–93. http://dx.doi.org/10.1109/jproc.2020.3043399.
45
Luo, Dan, Shuhua Xiong, Chao Ren, Raymond Edward Sheriff, and Xiaohai He. "Fusion-Based Versatile Video Coding Intra Prediction Algorithm with Template Matching and Linear Prediction." Sensors 22, no. 16 (August 10, 2022): 5977. http://dx.doi.org/10.3390/s22165977.
Abstract:
The new generation video coding standard Versatile Video Coding (VVC) has adopted many novel technologies to improve compression performance, and consequently, remarkable results have been achieved. In practical applications, less data, in terms of bitrate, would reduce the burden of the sensors and improve their performance. Hence, to further enhance the intra compression performance of VVC, we propose a fusion-based intra prediction algorithm in this paper. Specifically, to better predict areas with similar texture information, we propose a fusion-based adaptive template matching method, which directly takes the error between reference and objective templates into account. Furthermore, to better utilize the correlation between reference pixels and the pixels to be predicted, we propose a fusion-based linear prediction method, which can compensate for the deficiency of single linear prediction. We implemented our algorithm on top of the VVC Test Model (VTM) 9.1. When compared with the VVC, our proposed fusion-based algorithm saves a bitrate of 0.89%, 0.84%, and 0.90% on average for the Y, Cb, and Cr components, respectively. In addition, when compared with some other existing works, our algorithm showed superior performance in bitrate savings.
46
Lim, Sung-Chang, Dae-Yeon Kim, and Jungwon Kang. "Simplification on Cross-Component Linear Model in Versatile Video Coding." Electronics 9, no. 11 (November 9, 2020): 1885. http://dx.doi.org/10.3390/electronics9111885.
Abstract:
To improve coding efficiency by exploiting the local inter-component redundancy between the luma and chroma components, the cross-component linear model (CCLM) is included in the versatile video coding (VVC) standard. In the CCLM mode, linear model parameters are derived from the neighboring luma and chroma samples of the current block. Furthermore, chroma samples are predicted by the reconstructed samples in the collocated luma block with the derived parameters. However, as the CCLM design in the VVC test model (VTM)-6.0 has many conditional branches in its processes to use only available neighboring samples, the CCLM implementation in parallel processing is limited. To address this implementation issue, this paper proposes including the neighboring sample generation as the first process of the CCLM, so as to simplify the succeeding CCLM processes. As unavailable neighboring samples are replaced with the adjacent available samples by the proposed CCLM, the neighboring sample availability checks can be removed. This results in simplified downsampling filter shapes for the luma sample. Therefore, the proposed CCLM can be efficiently implemented by employing parallel processing in both hardware and software implementations, owing to the removal of the neighboring sample availability checks and the simplification of the luma downsampling filters. The experimental results demonstrate that the proposed CCLM reduces the decoding runtime complexity of the CCLM mode, with negligible impact on the Bjøntegaard delta (BD)-rate.
47
Acharjee, Suvojit, and Sheli Sinha Chaudhuri. "Test Zone Search Optimization Using Cuckoo Search Algorithm for VVC." International Journal of Multimedia Data Engineering and Management 13, no. 1 (January 1, 2022): 1–16. http://dx.doi.org/10.4018/ijmdem.314574.
Abstract:
Motion vector approximation is an integral part of every video coding standard to reduce temporal correlation. Estimating motion necessitates a lot of computation. Several attempts were made to reduce the computation cost in exhaustive search of motion estimation. Test zone search was accepted as benchmark algorithm for fast motion estimation by the most recent video coding standard, versatile video coding. Quality and speed of test zone search completely depends on two parameters (i.e., sub sampling frequency of search space during raster scan and dimension of the search space). Cuckoo search, one of the popular nature-inspired optimization algorithms, is used to optimize the operational parameters of test zone search. The proposed optimization enhanced the speed up to 50% while maintaining or improving the Bjontegaard rate (BD-Rate) and Bjontegaard PSNR (BDSNR).
48
Zhao, Jinchao, Peng Li, and Qiuwen Zhang. "A Fast Decision Algorithm for VVC Intra-Coding Based on Texture Feature and Machine Learning." Computational Intelligence and Neuroscience 2022 (September 13, 2022): 1–13. http://dx.doi.org/10.1155/2022/7675749.
Abstract:
Due to the development and application of information technology, a series of modern information technologies represented by 5G, big data, and artificial intelligence are changing rapidly, and people’s requirements for video coding standards have become higher. In the High-Efficiency Video Coding (HEVC) standard, the coding block division is not flexible enough, and the prediction mode is not detailed enough. A new generation of Versatile Video Coding (VVC) standards was born. VVC inherits the hybrid coding framework adopted by HEVC, improves the original technology of each module, introduces a series of new coding technologies, and builds on this greatly improving the coding efficiency. Compared with HEVC, the block division structure of VVC has undergone great changes, retaining the quad-tree (QT) division method and increasing the multi-type tree (MTT) division method, which brings high coding complexity. To reduce the computational complexity of VVC coding block division, a fast decision algorithm for VVC intra-frame coding based on texture characteristics and machine learning is proposed. First, we analyze the characteristics of the CU partition structure decision and then use the texture complexity of the CU partition structure decision to terminate the CU partition process early; for CUs that do not meet the early termination of the partition, use the global sample information, local sample information, and context information. The three-category feature-trained tandem classifier framework predicts the division type of CU. The experimental results show that in the full intra mode, compared with the existing VTM10.0, the encoding output bit rate is increased by 1.36%, and the encoding time is saved by 52.63%.
49
Wang, Ruyan, Liuwei Tang, and Tong Tang. "Fast Sample Adaptive Offset Jointly Based on HOG Features and Depth Information for VVC in Visual Sensor Networks." Sensors 20, no. 23 (November 26, 2020): 6754. http://dx.doi.org/10.3390/s20236754.
Abstract:
Visual sensor networks (VSNs) can be widely used in multimedia, security monitoring, network camera, industrial detection, and other fields. However, with the development of new communication technology and the increase of the number of camera nodes in VSN, transmitting and compressing the huge amounts of video and image data generated by video and image sensors has become a major challenge. The next-generation video coding standard—versatile video coding (VVC), can effectively compress the visual data, but the higher compression rate is at the cost of heavy computational complexity. Therefore, it is vital to reduce the coding complexity for the VVC encoder to be used in VSNs. In this paper, we propose a sample adaptive offset (SAO) acceleration method by jointly considering the histogram of oriented gradient (HOG) features and the depth information for VVC, which reduces the computational complexity in VSNs. Specifically, first, the offset mode selection (select band offset (BO) mode or edge offset (EO) mode) is simplified by utilizing the partition depth of coding tree unit (CTU). Then, for EO mode, the directional pattern selection is simplified by using HOG features and support vector machine (SVM). Finally, experimental results show that the proposed method averagely saves 67.79% of SAO encoding time only with 0.52% BD-rate degradation compared to the state-of-the-art method in VVC reference software (VTM 5.0) for VSNs.
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Li, Hongchan, Peng Zhang, Baohua Jin, and Qiuwen Zhang. "Fast CU Decision Algorithm Based on CNN and Decision Trees for VVC." Electronics 12, no. 14 (July 12, 2023): 3053. http://dx.doi.org/10.3390/electronics12143053.
Abstract:
Compared with the previous generation of High Efficiency Video Coding (HEVC), Versatile Video Coding (VVC) introduces a quadtree and multi-type tree (QTMT) partition structure with nested multi-class trees so that the coding unit (CU) partition can better match the video texture features. This partition structure makes the compression efficiency of VVC significantly improved, but the computational complexity is also significantly increased, resulting in an increase in encoding time. Therefore, we propose a fast CU partition decision algorithm based on DenseNet network and decision tree (DT) classifier to reduce the coding complexity of VVC and save more coding time. We extract spatial feature vectors based on the DenseNet network model. Spatial feature vectors are constructed by predicting the boundary probabilities of 4 × 4 blocks in 64 × 64 coding units. Then, using the spatial features as the input of the DT classifier, through the classification function of the DT classifier model, the top N division modes with higher prediction probability are selected, and other division modes are skipped to reduce the computational complexity. Finally, the optimal partition mode is selected by comparing the RD cost. Our proposed algorithm achieves 47.6% encoding time savings on VTM10.0, while BDBR only increases by 0.91%.