Local Objective Metrics of Blocking Artifacts Visibility for Adaptive Repair of Compressed Video Signals

2007 ◽  
Author(s):  
Ihor O. Kirenko ◽  
Ling Shao
Keyword(s):  
Compressed Video ◽  
Blocking Artifacts ◽  
Video Signals ◽  
Objective Metrics

scholarly journals Versatile Video Coding for 3.0 Next Generation Digital TV in Brazil

2021 ◽  
Vol 2021 (1) ◽  
pp. 9-17
Author(s):  
Thibaud Biatek ◽  
Mohsen Abdoli ◽  
Mickael Raulet ◽  
Adam Wieckowski ◽  
Christian Lehman ◽  
...  
Keyword(s):  
Video Coding ◽  
Compressed Video ◽  
Limited Bandwidth ◽  
Video Signals ◽  
4K Uhd ◽  
Time Encoding ◽  
Digital Broadcasting ◽  
Virtual And Augmented Reality ◽  
Video Broadcast ◽  
Successive Generations

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.

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 Compressed Video Quality Index Based on Saliency-Aware Artifact Detection

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6429
Author(s):  
Liqun Lin ◽  
Jing Yang ◽  
Zheng Wang ◽  
Liping Zhou ◽  
Weiling Chen ◽  
...  
Keyword(s):  
Saliency Detection ◽  
Video Quality ◽  
Video Stream ◽  
Support Vector ◽  
Compressed Video ◽  
Artifact Detection ◽  
Video Signals ◽  
Reference Information ◽  
Video Saliency ◽  
Video Quality Metric

Video coding technology makes the required storage and transmission bandwidth of video services decrease by reducing the bitrate of the video stream. However, the compressed video signals may involve perceivable information loss, especially when the video is overcompressed. In such cases, the viewers can observe visually annoying artifacts, namely, Perceivable Encoding Artifacts (PEAs), which degrade their perceived video quality. To monitor and measure these PEAs (including blurring, blocking, ringing and color bleeding), we propose an objective video quality metric named Saliency-Aware Artifact Measurement (SAAM) without any reference information. The SAAM metric first introduces video saliency detection to extract interested regions and further splits these regions into a finite number of image patches. For each image patch, the data-driven model is utilized to evaluate intensities of PEAs. Finally, these intensities are fused into an overall metric using Support Vector Regression (SVR). In experiment section, we compared the SAAM metric with other popular video quality metrics on four publicly available databases: LIVE, CSIQ, IVP and FERIT-RTRK. The results reveal the promising quality prediction performance of the SAAM metric, which is superior to most of the popular compressed video quality evaluation models.

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