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.

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>

PRIVACY INFORMATION PROTECTION IN AN ENCRYPTED COMPRESSED H.264 VIDEO BITSTREAM

2015 ◽  
Vol 3 (4) ◽  
pp. 343-345
Author(s):  
Pradeep Rajagopalan ◽  
Sanjay Kumar Gengaiyan
Keyword(s):  
Video Quality ◽  
Motion Vector ◽  
Video Stream ◽  
Security And Privacy ◽  
Original Video ◽  
Video Content ◽  
Compressed Video ◽  
High Data ◽  
Computation Efficiency ◽  
Wrapping Technique

The paper presents that encryption of compressed video bit streams and hiding privacy information to protect videos during transmission or cloud storage. Digital video sometimes needs to be stored and processed in an encrypted format to maintain security and privacy. Here, data hiding directly in the encrypted version of H.264/AVC video stream is approached, which includes the following three parts. By analyzing he property of H.264/AVC codec, the code words of intra prediction modes, the code words of motion vector differences, and the code words of residual coefficients are encrypted with stream ciphers. Then, a data hider may embed additional data in the encrypted domain by using wrapping technique, without knowing the original video content. The paper results shows that used methods provides better performance in terms of computation efficiency, high data security and video quality after decryption. The parameters such as RMSE, PSNR, CC are evaluated to measure its efficiency

Objective Video Quality Method Based on Mutual Information and Human Visual System

2012 ◽  
Vol 58 (2) ◽  
pp. 147-152
Author(s):  
Michal Mardiak ◽  
Jaroslav Polec
Keyword(s):  
Mutual Information ◽  
Visual System ◽  
Human Visual System ◽  
Quality Evaluation ◽  
Video Quality ◽  
Evaluation Criteria ◽  
Test Sequence ◽  
Quality Metric ◽  
Two Stages ◽  
Video Quality Metric

Objective Video Quality Method Based on Mutual Information and Human Visual SystemIn this paper we present the objective video quality metric based on mutual information and Human Visual System. The calculation of proposed metric consists of two stages. In the first stage of quality evaluation whole original and test sequence are pre-processed by the Human Visual System. In the second stage we calculate mutual information which has been utilized as the quality evaluation criteria. The mutual information was calculated between the frame from original sequence and the corresponding frame from test sequence. For this testing purpose we choose Foreman video at CIF resolution. To prove reliability of our metric were compared it with some commonly used objective methods for measuring the video quality. The results show that presented objective video quality metric based on mutual information and Human Visual System provides relevant results in comparison with results of other objective methods so it is suitable candidate for measuring the video quality.

An Improved Error Concealment Based on Redundant Motion Vector Information

2012 ◽  
Vol 532-533 ◽  
pp. 1219-1224
Author(s):  
Hong Tao Deng
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Video Quality ◽  
Motion Vector ◽  
Compressed Video ◽  
Vector Information ◽  
Vector Estimation ◽  
Channel Errors ◽  
Bit Stream

During video transmission over error prone network, compressed video bit-stream is sensitive to channel errors that may degrade the decoded pictures severely. In order to solve this problem, error concealment technique is a useful post-processing tool for recovering the lost information. In these methods, how to estimate the lost motion vector correctly is important for the quality of decoded picture. In order to recover the lost motion vector, an Decoder Motion Vector Estimation (DMVE) criterion was proposed and have well effect for recover the lost blocks. In this paper, we propose an improved error concealment method based on DMVE, which exploits the accurate motion vector by using redundant motion vector information. The experimental results with an H.264 codec show that our method improves both subjective and objective decoder reconstructed video quality, especially for sequences of drastic motion.

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