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Partition Map Prediction for Fast Block Partitioning in VVC intra-frame coding

IEEE TRANSACTIONS ON IMAGE PROCESSING 2023年 32卷 2237-2251页

作者： Feng, Aolin Liu, Kang Liu, Dong Li, Li Wu, Feng Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & App Hefei 230027 Peoples R China Univ Southern Calif Los Angeles CA 90007 USA

The Versatile Video coding (VVC) standard introduces a block partitioning structure known as quadtree plus nested multi-type tree (QTMTT), which allows more flexible block partitioning compared to its predecessors, like High Efficiency Video coding (HEVC). Meanwhile, the partition search (PS) process, which is to find out the best partitioning structure for optimizing the rate-distortion cost, becomes far more complicated for VVC than for HEVC. Also, the PS process in VVC reference software (VTM) is not friendly to hardware implementation. We propose a partition map prediction method for fast block partitioning in VVC intra-frame encoding. The proposed method may replace PS totally or be combined with PS partially, thereby achieving adjustable acceleration of the VTM intra-frame encoding. Different from the previous methods for fast block partitioning, we propose to represent a QTMTT-based block partitioning structure by a partition map, which consists of a quadtree (QT) depth map, several multi-type tree (MTT) depth maps, and several MTT direction maps. We then propose to predict the optimal partition map from the pixels through a convolutional neural network (CNN). We propose a CNN structure, known as Down-Up-CNN, for the partition map prediction, where the CNN structure emulates the recursive nature of the PS process. Moreover, we design a post-processing algorithm to adjust the network output partition map, so as to obtain a standard-compliant block partitioning structure. The post-processing algorithm may produce a partial partition tree as well;then based on the partial partition tree, the PS process is performed to obtain the full tree. Experimental results show that the proposed method achieves 1.61 x to 8.64 x encoding acceleration for the VTM-10.0 intra-frame encoder, with the ratio depending on how much PS is performed. Especially, when achieving 3.89 x encoding acceleration, the compression efficiency loss is 2.77% in BD-rate, which is a better tradeoff

关键词： Block partitioning convolutional neural network (CNN) fast algorithm intra-frame coding partition map partition search (PS) QTMTT versatile video coding (VVC)

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Efficient Low Bit-Rate intra-frame coding using Common Information for 360-degree Video 22

Efficient Low Bit-Rate Intra-Frame Coding using Common Infor...

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22nd IEEE International Workshop on Multimedia Signal Processing (MMSP)

作者： Afsana, Fariha Paul, Manoranjan Murshed, Manzur Taubman, David Charles Sturt Univ Sch Comp & Math Mitchell Australia Federat Univ Australia Fac Sci & Technol Ballarat Vic Australia Univ New South Wales Sch Elect Engn & Telecommun Kensington NSW Australia

ISBN: (纸本)9781728193205

With the growth of video technologies, super-resolution videos, including 360-degree immersive video has become a reality due to exciting applications such as augmented/virtual/mixed reality for better interaction and a wideangle user-view experience of a scene compared to traditional video with narrow-focused viewing angle. The new generation video contents are bandwidth-intensive in nature due to high resolution and demand high bit rate as well as low latency delivery requirements that pose challenges in solving the bottleneck of transmission and storage burdens. There is limited optimisation space in traditional video coding schemes for improving video coding efficiency in intra-frame due to the fixed size of processing block. This paper presents a new approach for improving intra-frame coding especially at low bit rate video transmission for 360-degree video for lossy mode of HEVC. Prior to using traditional HEVC intra-prediction, this approach exploits the global redundancy of entire frame by extracting common important information using multi-level discrete wavelet transformation. This paper demonstrates that the proposed method considering only low frequency information of a frame and encoding this can outperform the HEVC standard at low bit rates. The experimental results indicate that the proposed intra-frame coding strategy achieves an average of 54.07% BD-rate reduction and 2.84 dB BD-PSNR gain for low bit rate scenario compared to the HEVC. It also achieves a significant improvement in encoding time reduction of about 66.84% on an average. Moreover, this finding also demonstrates that the existing HEVC block partitioning can be applied in the transform domain for better exploitation of information concentration as we applied HEVC on wavelet frequency domain.

关键词： intra-frame coding 360-degree Video HEVC Discrete Wavelet Transform

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POSITION DEPENDENT PREDICTION COMBINATION FOR intra-frame VIDEO coding 23

POSITION DEPENDENT PREDICTION COMBINATION FOR INTRA-FRAME VI...

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23rd IEEE International Conference on Image Processing (ICIP)

作者： Said, Amir Zhao, Xin Karczewicz, Marta Chen, Jianle Zou, Feng Qualcomm Technol Inc San Diego CA 92121 USA

ISBN: (纸本)9781467399616

intra-frame prediction in the High Efficiency Video coding (HEVC) standard can be empirically improved by applying sets of recursive two-dimensional filters to the predicted values. However, this approach does not allow (or complicates significantly) the parallel computation of pixel predictions. In this work we analyze why the recursive filters are effective, and use the results to derive sets of non-recursive predictors that have superior performance. We present an extension to HEVC intra prediction that combines values predicted using non-filtered and filtered (smoothed) reference samples, depending on the prediction mode, and block size. Simulations using the HEVC common test conditions show that a 2.0% bit rate average reduction can be achieved compared to HEVC, for All intra (AI) configurations.

关键词： HEVC video coding linear prediction intra-frame coding

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Optimization of Depth Map intra coding Algorithms Based on Machine Learning

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IEEE ACCESS 2025年 13卷 5846-5857页

作者： Song, Wenjun Yang, Jiaying Zhang, Qiuwen Zhengzhou Univ Light Ind Coll Comp & Commun Engn Zhengzhou 450002 Peoples R China

As a cutting-edge field of global research, 3D video technology faces the dual challenges of large data volumes and high processing complexity. Although the most recent video coding standard VVC, surpasses HEVC in coding efficiency, dedicated research on 3D video coding remains relatively scarce. Building on existing research, this study aims to develop a 3D video coding algorithm based on VVC that lowers the complexity of the encoding procedure. We focus specifically on the depth maps in 3D video content and introduce an extreme forest model from machine learning to optimize intra-frame coding. This paper proposes a novel CU partitioning strategy implemented through a two-stage extreme forest model. First, the initial model predicts the CU partitioning type, including no partition, QuadTree partitioning, Multi-type tree horizontal partitioning, and Multi-type tree vertical partitioning. For the latter two cases, a second model further refines the partitioning into binary or ternary trees. Through this two-stage prediction mechanism, we effectively bypass CU partitioning types with low probability, significantly reducing the coding complexity. The experimental results demonstrate that the proposed algorithm saves 47.46% in encoding time while maintaining coding quality, with only a 0.26% increase in Bjontegaard Delta Bitrate. This achievement provides an effective low-complexity solution for the 3D video coding field.

关键词： Encoding Prediction algorithms Complexity theory Video coding Partitioning algorithms Three-dimensional displays Forestry Predictive models Adaptation models Classification algorithms Depth map intra-frame coding extreme forest

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IoT-Driven Visual Surveillance: Temporal Masking for Adaptive Motion Compensation in Imaging Technology

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2024年第4期70卷 7203-7211页

作者： Siddique, Ali Akbar Ghaban, Wad Aljaedi, Amer Saeed, Faisal Alshehri, Mohammad S. Alkhayyat, Ahmed Mobarak Albarakati, Hussain Sir Syed Univ Engn & Technol Dept Telecommun Engn Karachi 75300 Pakistan Univ Tabuk Appl Coll Tabuk 47512 Saudi Arabia Univ Tabuk Coll Comp & Informat Technol Tabuk 71491 Saudi Arabia Birmingham City Univ Coll Comp & Digital Technol DAAI Res Grp Birmingham B4 7XG England Najran Univ Coll Comp Sci & Informat Syst Dept Comp Sci Najran 61441 Saudi Arabia Islamic Univ Comp Engn Technol Dept Najaf 54001 Iraq Ummul Al Qura Univ Coll Comp Comp & Network Engn Dept Mecca 24382 Saudi Arabia

Global security is a matter of critical concern that requires adoption of advanced monitoring technologies. Efficient surveillance systems comprise extensive camera networks across large areas to ensure comprehensive coverage. However, the large volume of data generated by these networks poses challenges for traditional storage and computational resources. This paper presents an innovative video compression technique that focuses on optimizing data management in visual surveillance systems by selectively masking temporal information between frames. This technique introduces a specially designed adaptive masking filter, which hides the undetectable motion in video sequences and enhances video compression. The introduced masking technique uses an adaptive masking parameter 'q' to improve frame prediction or to compensate for the masked temporal activity during decoding and achieves over 30% bit-rate reduction compared to the standard video encoding schemes, such as H.264/AVC. Moreover, the introduced technique also reduces the computational demands while keeping the quality of the output. This can be evidenced by a Peak Signal to Noise Ratio (PSNR) of 33.67 dB and a Structural Similarity Index (SSIM) of 92.7% in a traffic video sequence. The proposed technique holds the potential to be used in efficient IoT-driven video surveillance systems to process video frames efficiently without compromising quality.

关键词： Streaming media Image coding Visualization Video sequences Consumer electronics Cameras Internet of Things intra-frame coding temporal masking adaptive motion compensation video surveillance imaging technology

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Performance analysis of VVC intra coding*

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2021年 79卷 103202-103202页

作者： Saldanha, Mario Sanchez, Gustavo Marcon, Cesar Agostini, Luciano Univ Fed Pelotas Pelotas RS Brazil IF Farroupilha Alegrete Brazil Pontificia Univ Catolica Rio Grande do Sul Porto Alegre RS Brazil

This article presents a performance analysis of Versatile Video coding (VVC) intra-frame prediction. VVC is the next generation of video coding standards, which has been developed to supply the demand of upcoming video applications. VVC brings several innovations and enhancements for the intra-frame prediction to improve the encoding efficiency. These improvements comprise larger block sizes, more flexible block partitioning, more angular intra-frame prediction modes, multiple transform selection, non-separable secondary transform, among others. This article provides a detailed description of these tools, discussing how they work together in the intraframe coding flow to raise the compression performance. Moreover, this article presents encoding complexity, encoding usage distribution, and rate-distortion-complexity analyses of the intra-frame prediction tools over different quantization scenarios. Based on these analyses, this article provides support for future works focusing on VVC intra-frame coding, including complexity reduction, complexity control, and real-time hardware design.

关键词： Versatile video coding VVC intra-frame coding Performance analysis

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Encounter CU Again: History-Based Complexity Reduction Strategy for VVC intra-frame Encoder 23

Encounter CU Again: History-Based Complexity Reduction Strat...

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23rd IEEE International Workshop on Multimedia Signal Processing (IEEE MMSP)

作者： Cao, Jian Jia, Yifan Liang, Fan Wang, Jun Sun Yat Sen Univ Sch Elect & Informat Technol Guangzhou Peoples R China Sun Yat Sen Univ Sch Microelect Sci & Technol Zhuhai Peoples R China Peng Cheng Lab Shenzhen Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai Zhuhai Peoples R China

ISBN: (纸本)9781665432870

Due to the newly adopted Quad Tree with Nested Multi-Type Tree (QTMT) partitioning scheme in Versatile Video coding (VVC), multiple partitioning combinations can lead to the same coding Unit (CU) structure. In other words, a CU may be encoded more than once. Based on this feature, a history-based complexity reduction strategy is proposed to accelerate VVC intra-frame coding with extremely low coding losses. Firstly, analyses of the relationship between the 1st round CUs (encoded at the first time) and the following rounds CUs (encountered again and already analyzed in previous partitioning attempts) are provided. Correspondingly, some unnecessary partitioning types are identified and early terminated. Secondly, a hierarchical pruning algorithm is designed, where thresholds are adjusted adaptively in the 1st round and used for pruning in the following rounds. To our knowledge, it is the first attempt to apply this history-based feature to accelerate partitioning for VVC intra-frame coding. Results show that these strategies can achieve 20% encoding time saving (TS) with only 0.18% BDBR increase. In addition, there is a huge potential for High-Resolution videos (21% TS with only 0.1% BDBR increase for 4K sequences). Compared to other works, our method achieves a considerably high TS/BDBR ratio, which indicates a better tradeoff between coding efficiency and complexity.

关键词： VVC intra-frame coding QTMT Complexity Reduction

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The Use of intra Prediction Method in Wavelet-Based Video coding Systems 22nd

The Use of Intra Prediction Method in Wavelet-Based Video Co...

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22nd International Conference on Distributed Computer and Communication Networks (DCCN)

作者： Verba, Gleb Bystrov, Kirill Dvorkovich, Viktor Gryzov, Gennady Moscow Inst Phys & Technol Inst Sky Lane 9 Dolgoprudnyi Russia

ISBN: (纸本)9783030366254;9783030366247

Modern image and video compression technologies include both lossless compression methods, such as entropy coding, Inter-frame and intra-frame coding, and lossy compression methods, such as discrete orthogonal transforms with quantization. All these techniques are actively applied in video codecs based on the H.264 and H.265 standards. Discrete wavelet transform (DWT) is one of the most perspective versions of discrete orthogonal transforms. Both intra-frame coding and wavelet decomposition of images allow to reduce the volume of transmitted data, but they are not used together in video coding systems. The combined usage of these methods seems to be a promising approach in terms of visual data compression. Thereby the aim of this research is to develop a new technique based on the combination of intra-frame coding and the DWT and to test the applicability of the proposed method in the image compression tasks. The effectiveness of various implementations of the proposed algorithm, including those based on contexts and using several levels of wavelet decomposition of images, was evaluated in the study.

关键词： intra Prediction intra-frame coding Discrete wavelet transform Video coding Data compression Context-based coding

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Research on a Parallel Rate Control Algorithm of Macro-Block Layer 15th

Research on a Parallel Rate Control Algorithm of Macro-Block...

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15th International Forum on Digital TV and Multimedia Communication (IFTC)

作者： Ding, Min Huang, Lulu Li, Guoping Wang, Guozhong Shanghai Univ Sch Commun & Informat Engn Shanghai 200444 Peoples R China

ISBN: (纸本)9789811381386;9789811381379

In order to efficiently transmit video data while satisfying the channel bandwidth and transmission delay constraints, bit rate control of the video encoding process is required. According to ultra-high-definition video, traditional coding algorithms have a large amount of caculation and high computational complexity, thus, parallel coding methods such as inter-frame parallel coding and wavefront parallel coding (WPP) are proposed. However, the rate control of parallel coding is a difficult problem, especially the intra-frame rate control under the WPP coding mode, so this paper proposes a bit rate control algorithm within macro-block layer. By contrasting the PSNR, the encoding speed and the VBV (Video Buffer Verifier) buffer condition of the video sequences, the algorithm proposed in this paper has advantages of less computing cost and faster coding speed than the traditional algorithms.

关键词： Parallel coding Rate control intra-frame coding Quantization parameter Wavefront parallel processing

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Deep neural network based single pixel prediction for unified video coding

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NEUROCOMPUTING 2018年 272卷 558-570页

作者： Li, Honggui Trocan, Maria Yangzhou Univ Phys Coll Sci & Technol Yangzhou 225002 Jiangsu Peoples R China Inst Super Elect Paris Lab Informat Signal & Image Telecommun & Elect F-75006 Paris France

Classical video prediction methods exploit directly and shallowly the intra-frame, inter-frame and multi-view similarities within the video sequences;the proposed video prediction methods indirectly and intensively transform the frame correlations into nonlinear mappings by using a general deep neural network (DNN) with single output node. Traditional DNN based video prediction algorithms wholly and coarsely forecast the next frame, but the proposed video prediction algorithms severally and precisely anticipate single pixel of future frame in order to achieve high prediction accuracy and low computation cost. First of all, general DNN based prediction algorithms for intra-frame coding, inter-frame coding and multi-view coding are presented respectively. Then, general DNN based prediction algorithm for unified video coding is raised, which relies on the preceding three prediction algorithms. It is evaluated by simulation experiments that the proposed methods hold better performance than state of the art High Efficiency Video coding (HEVC) in peak signal to noise ratio (PSNR) and bit per pixel (BPP) in the situation of low bitrate transmission. It is also verified by experimental results that the proposed general DNN architecture possesses higher prediction accuracy and lower computation load than those of conventional DNN architectures. It is further testified by experimental results that the proposed methods are very suitable for multi-view videos with small correlations and big disparities. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Deep neural network Video prediction Unified video coding intra-frame coding Inter-frame coding Multi-view coding

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