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.

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.

scholarly journals Video Compression for Screen Recorded Sequences Following Eye Movements

2021 ◽  
Author(s):  
Diego Jesus Serrano-Carrasco ◽  
Antonio Jesus Diaz-Honrubia ◽  
Pedro Cuenca
Keyword(s):  
Eye Tracking ◽  
Video Coding ◽  
Video Compression ◽  
High Performance ◽  
High Efficiency ◽  
Tracking System ◽  
Bit Rate ◽  
Video Traffic ◽  
High Efficiency Video Coding ◽  
Perceptual Video Coding

AbstractWith the advent of smartphones and tablets, video traffic on the Internet has increased enormously. With this in mind, in 2013 the High Efficiency Video Coding (HEVC) standard was released with the aim of reducing the bit rate (at the same quality) by 50% with respect to its predecessor. However, new contents with greater resolutions and requirements appear every day, making it necessary to further reduce the bit rate. Perceptual video coding has recently been recognized as a promising approach to achieving high-performance video compression and eye tracking data can be used to create and verify these models. In this paper, we present a new algorithm for the bit rate reduction of screen recorded sequences based on the visual perception of videos. An eye tracking system is used during the recording to locate the fixation point of the viewer. Then, the area around that point is encoded with the base quantization parameter (QP) value, which increases when moving away from it. The results show that up to 31.3% of the bit rate may be saved when compared with the original HEVC-encoded sequence, without a significant impact on the perceived quality.

scholarly journals Video Quality Assessment through PSNR Estimation for Different Compression Standards

2018 ◽  
Vol 11 (3) ◽  
pp. 918 ◽  
Author(s):  
Renuka Girish Deshpande ◽  
Lata L Ragha ◽  
Satyendra Kumar Sharma
Keyword(s):  
Video Compression ◽  
Video Quality ◽  
Compressed Video ◽  
Video Traffic ◽  
Subjective Analysis ◽  
Video Signals ◽  
Interesting Task ◽  
Set Up ◽  
The Cost

<p align="center"><strong><em>Abstract</em></strong></p><p><em>           There is a threefold increase in video traffic over internet. Due to this video compression has become important. Compression of video signals is quiet an interesting task but comes at the cost of video quality. After compression, two methods are scientifically applied to evaluate the quality of video; Subjective and objective analysis. In subjective approach the compressed video is shown to a group of viewers and their feedback is recorded Objective approach aims to set up a mathematical model which can approximate the results of subjective analysis. One such approach is based on the measurement of PSNR. When a signal is applied to the encoder for compression, too much of compression results in a signal with a smaller size but at the same time quality of the signal degrades. In this paper we will compare the quality of compressed video signals produced by H.264, Mpeg2 and Mpeg4 encoder based on the values of MSE and PSNR. Lower the value of MSE, higher will be the PSNR. Comparative plots of MSE, PSNR, SSIM and images for subjective analysis have been added at the end of this paper. </em></p>

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 A Motion Estimation based Algorithm for Encoding Time Reduction in HEVC

2022 ◽  
Vol 72 (1) ◽  
pp. 56-66
Author(s):  
S. Karthik Sairam ◽  
P. Muralidhar
Keyword(s):  
Motion Estimation ◽  
Video Coding ◽  
Video Compression ◽  
High Efficiency ◽  
Search Algorithm ◽  
Video Quality ◽  
Search Pattern ◽  
Absolute Difference ◽  
High Efficiency Video Coding ◽  
Search Patterns

High Efficiency Video Coding (HEVC) is a video compression standard that offers 50% more efficiency at the expense of high encoding time contrasted with the H.264 Advanced Video Coding (AVC) standard. The encoding time must be reduced to satisfy the needs of real-time applications. This paper has proposed the Multi- Level Resolution Vertical Subsampling (MLRVS) algorithm to reduce the encoding time. The vertical subsampling minimizes the number of Sum of Absolute Difference (SAD) computations during the motion estimation process. The complexity reduction algorithm is also used for fast coding the coefficients of the quantised block using a flag decision. Two distinct search patterns are suggested: New Cross Diamond Diamond (NCDD) and New Cross Diamond Hexagonal (NCDH) search patterns, which reduce the time needed to locate the motion vectors. In this paper, the MLRVS algorithm with NCDD and MLRVS algorithm with NCDH search patterns are simulated separately and analyzed. The results show that the encoding time of the encoder is decreased by 55% with MLRVS algorithm using NCDD search pattern and 56% with MLRVS using NCDH search pattern compared to HM16.5 with Test Zone (TZ) search algorithm. These results are achieved with a slight increase in bit rate and negligible deterioration in output video quality.

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.

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