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>

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.

scholarly journals A Mobile Fog Computing-Assisted DASH QoE Prediction Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Hongyun Zheng ◽  
Yongxiang Zhao ◽  
Xi Lu ◽  
Rongzhen Cao
Keyword(s):  
Quality Of Experience ◽  
Fog Computing ◽  
Video Quality ◽  
Adaptive Streaming ◽  
Network Operator ◽  
Video Traffic ◽  
Client Server ◽  
Prediction Scheme ◽  
Network Equipment

Video service has become a killer application for mobile terminals. For providing such services, most of the traffic is carried by the Dynamic Adaptive Streaming over HTTP (DASH) technique. The key to improve video quality perceived by users, i.e., Quality of Experience (QoE), is to effectively characterize it by using measured data. There have been many literatures that studied this issue. Some existing solutions use probe mechanism at client/server, which, however, are not applicable to network operator. Some other solutions, which aimed to predict QoE by deep packet parsing, cannot work properly as more and more video traffic is encrypted. In this paper, we propose a fog-assisted real-time QoE prediction scheme, which can predict the QoE of DASH-supported video streaming using fog nodes. Neither client/server participations nor deep packet parsing at network equipment is needed, which makes this scheme easy to deploy. Experimental results show that this scheme can accurately detect QoE with high accuracy even when the video traffic is encrypted.

scholarly journals Video Quality of Experience Metric for Dynamic Adaptive Streaming Services Using DASH Standard and Deep Spatial-Temporal Representation of Video

2020 ◽  
Vol 10 (5) ◽  
pp. 1793
Author(s):  
Lina Du ◽  
Li Zhuo ◽  
Jiafeng Li ◽  
Jing Zhang ◽  
Xiaoguang Li ◽  
...  
Keyword(s):  
Video Compression ◽  
Quality Of Experience ◽  
Feature Vector ◽  
Video Quality ◽  
Superior Performance ◽  
Adaptive Streaming ◽  
Input Feature ◽  
Streaming Services ◽  
Content Characteristics

DASH (Dynamic Adaptive Streaming over HTTP (HyperText Transfer Protocol)) as a universal unified multimedia streaming standard selects the appropriate video bitrate to improve the user’s Quality of Experience (QoE) according to network conditions, client status, etc. Considering that the quantitative expression of the user’s QoE is also a difficult point in itself, this paper researched the distortion caused due to video compression, network transmission and other aspects, and then proposes a video QoE metric for dynamic adaptive streaming services. Three-Dimensional Convolutional Neural Networks (3D CNN) and Long Short-Term Memory (LSTM) are used together to extract the deep spatial-temporal features to represent the content characteristics of the video. While accounting for the fluctuation in the quality of a video caused by bitrate switching on the QoE, other factors such as video content characteristics, video quality and video fluency, are combined to form the input feature vector. The ridge regression method is adopted to establish a QoE metric that enables to dynamically describe the relationship between the input feature vector and the value of the Mean Opinion Score (MOS). The experimental results on different datasets demonstrate that the prediction accuracy of the proposed method can achieve superior performance over the state-of-the-art methods, which proves the proposed QoE model can effectively guide the client’s bitrate selection in dynamic adaptive streaming media services.

Analysis on the Rotary Inertial of the Primary Pump for China Advanced Research Reactor

2008 ◽  
Author(s):  
Jia Zhong ◽  
Wenxi Tian ◽  
Shengyao Jiang
Keyword(s):  
Research Reactor ◽  
Reactor Core ◽  
Physical Models ◽  
Rotary Inertia ◽  
Fortran Language ◽  
Set Up ◽  
Under Construction ◽  
The Cost ◽  
Residual Heat

The rotary inertia of the reactor’s primary pump is an important factor related to the reactor’s safety under some accidental conditions. If the rotary inertia of the primary pump is big, that the pump’s inertia time will be long and the coolant mass flow rate will decrease slowly. So it is helpful to remove the residual heat and enhance the safety of the reactor. On the other hand, a bigger rotary inertia increases the cost, and causes some other inconvenience. In this paper, our research object is China Advanced Research Reactor (CARR) which is under construction. Systemic mathematical and physical models were set up and a program was developed using FORTRAN language with GEAR numerical method to analyze the transient of CARR. The primary thermal-hydraulic parameters of the reactor core were obtained in case of loss of power accident under different rotary inertia of the pump. These parameters include the temperature of the coolant the clad and the fuel, the maximal quality of the reactor core and MDNBR, etc. On the basis of the calculate result, it can be found that when the rotary inertia of the pump is larger than 150 Kg·m2, all of the thermal parameters in loss of power accident meet the safety requirement. And if the rotary inertia of the pump is 450 Kg·m2 which is the design value of CARR, the delay shutdown time in loss of power accident must not exceed 20 seconds.

scholarly journals An experimental survey of no-reference video quality assessment methods

2016 ◽  
Vol 12 (1) ◽  
pp. 66-86 ◽  
Author(s):  
Maria Torres Vega ◽  
Vittorio Sguazzo ◽  
Decebal Constantin Mocanu ◽  
Antonio Liotta
Keyword(s):  
Video Compression ◽  
Video Quality ◽  
Video Data ◽  
Original Video ◽  
Data Set ◽  
Content Type ◽  
Quality Metric ◽  
Simulated Network ◽  
Video Quality Metric

Purpose The Video Quality Metric (VQM) is one of the most used objective methods to assess video quality, because of its high correlation with the human visual system (HVS). VQM is, however, not viable in real-time deployments such as mobile streaming, not only due to its high computational demands but also because, as a Full Reference (FR) metric, it requires both the original video and its impaired counterpart. In contrast, No Reference (NR) objective algorithms operate directly on the impaired video and are considerably faster but loose out in accuracy. The purpose of this paper is to study how differently NR metrics perform in the presence of network impairments. Design/methodology/approach The authors assess eight NR metrics, alongside a lightweight FR metric, using VQM as benchmark in a self-developed network-impaired video data set. This paper covers a range of methods, a diverse set of video types and encoding conditions and a variety of network impairment test-cases. Findings The authors show the extent by which packet loss affects different video types, correlating the accuracy of NR metrics to the FR benchmark. This paper helps identifying the conditions under which simple metrics may be used effectively and indicates an avenue to control the quality of streaming systems. Originality/value Most studies in literature have focused on assessing streams that are either unaffected by the network (e.g. looking at the effects of video compression algorithms) or are affected by synthetic network impairments (i.e. via simulated network conditions). The authors show that when streams are affected by real network conditions, assessing Quality of Experience becomes even harder, as the existing metrics perform poorly.

scholarly journals Setup Changeover Time Reduction in 4 Wheel Drive Front Axle Differential Case Cone Bearing Pressing Process – SMED Method

2019 ◽  
Vol 9 (1S4) ◽  
pp. 944-947
Keyword(s):  
Operating Cost ◽  
Front Axle ◽  
Manufacturing Operations ◽  
Wheel Drive ◽  
Time Reduction ◽  
Set Up ◽  
The Cost ◽  
Assembly Production ◽  
Real Challenge

Single minute Exchange of Die is one of the LEAN approach to reduce the set up change over time and seven kind of losses due to the weakness in the initial process customization. Manufacturing organizations faces problem in reduction of cost and increasing the efficiency or productivity which is real challenge in the manufacturing operations. In the highly competitive or globalized society the manufacturer need to find a method to reduce the cost and production time to reduce the operating cost and Quality of product and Reliability. This paper deals with the basic over view of a reduction in set up time in a sub assembly stage of an auto sector by Setup Changeover Time Reduction (SMED). It is definitely possible to reduce the set up times and cost of sub assembly production considerably by simple modifications or improvements. The reduction of set up time can be done with the help of SMED methodology. Various types of industries can apply the SMED Methodology to reduce their set up times.

An Efficient Video Compression Encoder Based on Wavelet Lifting Scheme in LSK

2016 ◽  
Vol 13 (10) ◽  
pp. 7581-7591
Author(s):  
S. Anantha Padmanabhan ◽  
Krishna Kumar
Keyword(s):  
Wavelet Transform ◽  
Video Compression ◽  
Video Quality ◽  
Lifting Scheme ◽  
Estimation Algorithm ◽  
Discrete Wavelet ◽  
Discrete Cosine Transforms ◽  
Video Signals ◽  
Gradient Based ◽  
Wavelet Lifting

This paper presents a video compression system using wavelet lifting scheme. Video compression algorithms (“codecs”) manipulate video signals to dramatically reduce the storage and bandwidth required while maximizing the perceived video quality. There are four common methods for compression; discrete cosine transforms (DCT), vector quantization (VQ), fractal compression, and discrete wavelet transform (DWT). A gradient based motion estimation algorithm based on shapemotion prediction is used which takes advantage of the correlation between neighboring Binary Alpha Blocks (BABs), to match with the MPEG-4 shape coding case and speed up the estimation process. Then a non-redundant wavelet transform has been implemented as an iterative filter banks with down sampling operations. LSK operates without lists and is suitable for a fast, simple hardware implementation. Here the Set Partitioned Embedded bloCK coder (SPECK) image compression called Improved Listless SPECK (ILSPECK) is used. ILSPECK code a single zero to several insignificant subbands. This reduces the length of the output bit string as well as encoding/decoding time.

New Approach of Encrypting Embedded Data in H.264 Compressed Video

2011 ◽  
Vol 230-232 ◽  
pp. 346-351
Author(s):  
Tarik Idbeaa ◽  
Kasmiran Jumari ◽  
Salina Abd. Samad ◽  
Ali Abdulgader ◽  
Nidal Eshah
Keyword(s):  
Video Coding ◽  
Video Compression ◽  
Signal To Noise Ratio ◽  
Video Stream ◽  
Video Sequences ◽  
Compressed Video ◽  
Signal To Noise ◽  
New Approach ◽  
Video Steganography

Digital video steganography has attracted a great deal of research interest in the recent few years in applications. In this paper, we propose a method to embed and encrypt messages into video sequences by using steganography technique Based on the H.264 video coding standard. The system implemented in this work provides robust H.264 video compression constant, without significantly affecting the overall bit rate and quality of the video stream. The results indicate that the algorithm can be implemented steganography fast and efficiently and effect vision and peak signal to noise ratio (PSNR) of video sequences are almost unaffected after decoding.

scholarly journals A Novel Traffic Rate Measurement Algorithm for Quality of Experience-Aware Video Admission Control

2020 ◽  
Author(s):  
Alexander A. Kist ◽  
qahhar muhammad qadir ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Service Providers ◽  
Video Quality ◽  
The Internet ◽  
Video Traffic ◽  
Internet Service ◽  
Trade Off ◽  
Available Bandwidth ◽  
Traffic Rate

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.

scholarly journals A quality of experience-aware cross-layer architecture for optimizing video streaming services

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Video Streaming ◽  
Quality Of Experience ◽  
Video Quality ◽  
The Internet ◽  
Cross Layer ◽  
Video Traffic ◽  
Adaptive Architecture ◽  
Streaming Services ◽  
Simulation Results

The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture ).

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