scholarly journals An Overview of Coding Tools in AV1: the First Video Codec from the Alliance for Open Media

2020 ◽  
Vol 9 ◽  
Author(s):  
Yue Chen ◽  
Debargha Mukherjee ◽  
Jingning Han ◽  
Adrian Grange ◽  
Yaowu Xu ◽  
...  
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
State Of The Art ◽  
Video Codec ◽  
Compression Tests ◽  
Video Technology ◽  
Compression Efficiency ◽  
Test Set ◽  
Decoding Complexity ◽  
Performance Gains

Abstract In 2018, the Alliance for Open Media (AOMedia) finalized its first video compression format AV1, which is jointly developed by the industry consortium of leading video technology companies. The main goal of AV1 is to provide an open source and royalty-free video coding format that substantially outperforms state-of-the-art codecs available on the market in compression efficiency while remaining practical decoding complexity as well as being optimized for hardware feasibility and scalability on modern devices. To give detailed insights into how the targeted performance and feasibility is realized, this paper provides a technical overview of key coding techniques in AV1. Besides, the coding performance gains are validated by video compression tests performed with the libaom AV1 encoder against the libvpx VP9 encoder. Preliminary comparison with two leading HEVC encoders, x265 and HM, and the reference software of VVC is also conducted on AOM's common test set and an open 4k set.

scholarly journals The Influence of Coding Tools on Immersive Video Coding

2021 ◽  
Author(s):  
Jakub Szekiełda ◽  
Adrian Dziembowski ◽  
Dawid Mieloch
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Video Codec ◽  
Experimental Results ◽  
High Efficiency Video Coding ◽  
Video Encoder ◽  
Typical Configuration

This paper summarizes the research on the influence of HEVC (High Efficiency Video Coding) configuration on immersive video coding. The research was focused on the newest MPEG standard for immersive video compression – MIV (MPEG Immersive Video). The MIV standard is used as a preprocessing step before the typical video compression thus is agnostic to the video codec. Uncommon characteristics of videos produced by MIV causes, that the typical configuration of the video encoder (optimized for compression of natural sequences) is not optimal for such content. The experimental results prove, that the performance of video compression for immersive video can be significantly increased when selected coding tools are being used.

scholarly journals Review on Architectures of Motion Estimation for Video Coding Standards

2018 ◽  
Vol 7 (4.10) ◽  
pp. 928
Author(s):  
Prayline Rajabai C ◽  
Sivanantham S
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Video Compression ◽  
Video Data ◽  
Video Codec ◽  
Current Frame ◽  
Estimation Algorithms ◽  
Hardware Architectures ◽  
Coding Standards ◽  
Extensive Computation

Various video coding standards like H.264 and H.265 are used for video compression and decompression. These coding standards use multiple modules to perform video compression. Motion Estimation (ME) is one of the critical blocks in the video codec which requires extensive computation. Hence it is computationally complex, it critically consumes a massive amount of time to process the video data. Motion Estimation is the process which improves the compression efficiency of these coding standards by determining the minimum distortion between the current frame and the reference frame. For the past two decades, various Motion Estimation algorithms are implemented in hardware and research is still going on for realizing an optimized hardware solution for this critical module. Efficient implementation of ME in hardware is essential for high-resolution video applications such as HDTV to increase the decoding throughput and to achieve high compression ratio. A review and analysis of various hardware architectures of ME used for H.264 and H.265 coding standards is presented in this paper.  

Using Multiscale Edge Detection for Low Bit-Rate Subband Video Coding

2012 ◽  
Author(s):  
Mohsen Ashourian ◽  
Zulkalnain Mohd. Yusof ◽  
Sheikh Hussain S. Salleh ◽  
Syed Abd. Rahman S. A. Bakar
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Three Dimensional ◽  
Spatial Filter ◽  
Video Codec ◽  
Bit Rate ◽  
Low Bit Rate ◽  
Video Frames ◽  
Tele Monitoring ◽  
Efficient Selection

This paper introduces a video compression system for very low bit–rate video–conferencing and tele–monitoring applications. The video codec first performs a three–dimensional subband decomposition on a group of video frames, and then encode the subbands with different quantization methods. By using a cubic spline wavelet, the spatial filter bank acts as a multiscale edge detector. This property is used for efficient selection and coding of high frequency subbands with geometric vector quantization. For lowest tempo–spatial subband, a DPCM coding with an entropy coder was used. Results at several low bit rates (16,32, 64, 128 Kbps) are reported and compared with H.263, the standard for low bit rate video coding.

scholarly journals Load Balancing Strategies for Slice-Based Parallel Versions of JEM Video Encoder

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 320
Author(s):  
Héctor Migallón ◽  
Otoniel López-Granado ◽  
Miguel O. Martínez-Rach ◽  
Vicente Galiano ◽  
Manuel P. Malumbres
Keyword(s):  
Load Balancing ◽  
Video Coding ◽  
Shared Memory ◽  
Video Compression ◽  
Software Package ◽  
Video Quality ◽  
Depth Resolution ◽  
Test Model ◽  
Video Traffic ◽  
Compression Efficiency

The proportion of video traffic on the internet is expected to reach 82% by 2022, mainly due to the increasing number of consumers and the emergence of new video formats with more demanding features (depth, resolution, multiview, 360, etc.). Efforts are therefore being made to constantly improve video compression standards to minimize the necessary bandwidth while retaining high video quality levels. In this context, the Joint Collaborative Team on Video Coding has been analyzing new video coding technologies to improve the compression efficiency with respect to the HEVC video coding standard. A software package known as the Joint Exploration Test Model has been proposed to implement and evaluate new video coding tools. In this work, we present parallel versions of the JEM encoder that are particularly suited for shared memory platforms, and can significantly reduce its huge computational complexity. The proposed parallel algorithms are shown to achieve high levels of parallel efficiency. In particular, in the All Intra coding mode, the best of our proposed parallel versions achieves an average efficiency value of 93.4%. They also had high levels of scalability, as shown by the inclusion of an automatic load balancing mechanism.

Dirac Video Codec

2011 ◽  
pp. 58-94
Author(s):  
Kok Keong ◽  
Myo Tun ◽  
Yoong Choon Chang
Keyword(s):  
Video Coding ◽  
Data Storage ◽  
Video Compression ◽  
Rate Distortion ◽  
Video Codec ◽  
Discrete Wavelet ◽  
Coding System ◽  
Web Content ◽  
Video Codecs ◽  
Block Based

Dirac was started off by British Broadcasting Corp. (BBC) in 2003 as an experimental video coding system based on wavelet technology, which is different from that used in the main proprietary/standard video compression systems. Over the years, Dirac has grown out of its initial development and it is now on offer as an advanced royalty-free video coding system designed for a wide range of users, from delivering low-resolution web content to broadcasting high-definition (HD) and beyond, to near-lossless studio editing. The Dirac’s video coding architecture and algorithms are designed with the “keep it simple” mindset. In spite of that the Dirac seems to give a two-fold reduction in bitrate over MPEG-2 for HD video and broadly competitive with state-of-the-art video codecs. This chapter introduces the architecture of Dirac video encoder. The overall encoding structure is discussed followed by the detail description of motion estimation, Overlapped Block-based Motion Compensation (OBMC), Discrete Wavelet Transform (DWT), Rate Distortion Optimization (RDO) quantization and entropy coding. The Dirac’s bitstream syntax for compressed video data storage and streaming is described. Besides that, the coding performance of Dirac in terms of compression ratio, PSNR, SSIM and VQM in comparison with H.264 as a reference are discussed. Related issues such as transcoding and streaming over packat erasure channel are also discussed.

scholarly journals Compression efficiency analysis of AV1, VVC, and HEVC for random access applications

2021 ◽  
Vol 10 ◽  
Author(s):  
Tung Nguyen ◽  
Detlev Marpe
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Random Access ◽  
Bit Rate ◽  
High Efficiency Video Coding ◽  
Compression Efficiency ◽  
Coding Schemes ◽  
Specific Frequency ◽  
Different Characteristics

AOM Video 1 (AV1) and Versatile Video Coding (VVC) are the outcome of two recent independent video coding technology developments. Although VVC is the successor of High Efficiency Video Coding (HEVC) in the lineage of international video coding standards jointly developed by ITU-T and ISO/IEC within an open and public standardization process, AV1 is a video coding scheme that was developed by the industry consortium Alliance for Open Media (AOM) and that has its technological roots in Google's proprietary VP9 codec. This paper presents a compression efficiency evaluation for the AV1, VVC, and HEVC video coding schemes in a typical video compression application requiring random access. The latter is an important property, without which essential functionalities in digital video broadcasting or streaming could not be provided. For the evaluation, we employed a controlled experimental environment that basically follows the guidelines specified in the Common Test Conditions of the Joint Video Experts Team. As representatives of the corresponding video coding schemes, we selected their freely available reference software implementations. Depending on the application-specific frequency of random access points, the experimental results show averaged bit-rate savings of about 10–15% for AV1 and 36–37% for the VVC reference encoder implementation (VTM), both relative to the HEVC reference encoder implementation (HM) and by using a test set of video sequences with different characteristics regarding content and resolution. A direct comparison between VTM and AV1 reveals averaged bit-rate savings of about 25–29% for VTM, while the averaged encoding and decoding run times of VTM relative to those of AV1 are around 300% and 270%, respectively.

scholarly journals Impact of Scene Content on High Resolution Video Quality

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2872
Author(s):  
Miroslav Uhrina ◽  
Anna Holesova ◽  
Juraj Bienik ◽  
Lukas Sevcik
Keyword(s):  
Video Compression ◽  
Spatial Information ◽  
Video Quality ◽  
Video Sequences ◽  
Compression Efficiency ◽  
Opinion Score ◽  
Scene Description ◽  
Two Parameters ◽  
The University ◽  
The Impact

This paper deals with the impact of content on the perceived video quality evaluated using the subjective Absolute Category Rating (ACR) method. The assessment was conducted on eight types of video sequences with diverse content obtained from the SJTU dataset. The sequences were encoded at 5 different constant bitrates in two widely video compression standards H.264/AVC and H.265/HEVC at Full HD and Ultra HD resolutions, which means 160 annotated video sequences were created. The length of Group of Pictures (GOP) was set to half the framerate value, as is typical for video intended for transmission over a noisy communication channel. The evaluation was performed in two laboratories: one situated at the University of Zilina, and the second at the VSB—Technical University in Ostrava. The results acquired in both laboratories reached/showed a high correlation. Notwithstanding the fact that the sequences with low Spatial Information (SI) and Temporal Information (TI) values reached better Mean Opinion Score (MOS) score than the sequences with higher SI and TI values, these two parameters are not sufficient for scene description, and this domain should be the subject of further research. The evaluation results led us to the conclusion that it is unnecessary to use the H.265/HEVC codec for compression of Full HD sequences and the compression efficiency of the H.265 codec by the Ultra HD resolution reaches the compression efficiency of both codecs by the Full HD resolution. This paper also includes the recommendations for minimum bitrate thresholds at which the video sequences at both resolutions retain good and fair subjectively perceived quality.

Fuzzy Holoentropy-Based Adaptive Inter-Prediction Mode Selection for H.264 Video Coding

2019 ◽  
Vol 10 (2) ◽  
pp. 42-60
Author(s):  
Srinivas Bachu ◽  
N. Ramya Teja
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
Mode Selection ◽  
Rate Distortion ◽  
Computation Time ◽  
Exhaustive Search ◽  
Inter Prediction ◽  
Major Drawback ◽  
Prediction Mode

Due to the advancement of multimedia and its requirement of communication over the network, video compression has received much attention among the researchers. One of the popular video codings is scalable video coding, referred to as H.264/AVC standard. The major drawback in the H.264 is that it performs the exhaustive search over the interlayer prediction to gain the best rate-distortion performance. To reduce the computation overhead due to exhaustive search on mode prediction process, this paper presents a new technique for inter prediction mode selection based on the fuzzy holoentropy. This proposed scheme utilizes the pixel values and probabilistic distribution of pixel symbols to decide the mode. The adaptive mode selection is introduced here by analyzing the pixel values of the current block to be coded with those of a motion compensated reference block using fuzzy holoentropy. The adaptively selected mode decision can reduce the computation time without affecting the visual quality of frames. Experimentation of the proposed scheme is evaluated by utilizing five videos, and from the analysis, it is evident that proposed scheme has overall high performance with values of 41.367 dB and 0.992 for PSNR and SSIM respectively.

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