Network Video Quality Research Articles

The analysis of network video quality assessment based on different fuzzy neural network

The analysis of network video quality assessment based on different fuzzy neural network

Server-side adaptive bitrate method based on perceptual video quality in networks with controllable bandwidth

In HTTP adaptive bitrate (ABR) streaming, the ABR algorithm is an important factor determining the quality of experience. Traditional ABR methods control the bitrate of individual clients autonomously so that the quality variation occurs even when the bandwidth of a delivery network is managed. Here, we propose a server-side ABR method achieving quality fairness among clients and suppressing a quality variation over time in networks where external applications dynamically control the quality of service. The method controls both the bitrate and delivery bandwidth based on a perceptual quality score. We evaluated the basic performance of the proposed method on an experimental network whose bandwidth could be controlled by the API. We confirmed that the proposed method could maintain the target quality within the upper-limit bandwidth and suppress the quality variation among clients and over time.

Using Fuzzy Neural Network to Assess Network Video Quality

Using Fuzzy Neural Network to Assess Network Video Quality

The optimization network video quality assessment method based on fuzzy inference

The optimization network video quality assessment method based on fuzzy inference

Network video quality assessment method using fuzzy decision tree

At present the service of network video is increasing rapidly. The video quality of experience is usually defined as user experience. However, the objective quality assessment for network video is unsure but is an urgent need. To improve the objective method, this study proposes an assessment method using a fuzzy decision tree. This work has two parts: (i) It considers different impair factors. Next, the decision tree is built by the set of measured factors from the different network environments. This tree can define the quality of network video, but cannot give the concrete objective scores. (ii) In order to give the accuracy objective scores, all the impair factors of leaf nodes are divided into two groups and inputted to fuzzy logic systems. The outputs are used as the next inputs and inputted into another fuzzy logic system to give the objective score. At last, the performance of the proposed method is tested on network videos with different network environments. At the same time, other methods are compared with it. The experimental results show that this method can get more accurate objective scores. This means the proposed method can improve the objective assessment model.

Impact of GoP on the Video Quality of VP9 Compression Standard for Full HD Resolution

In the last years, the interest on multimedia services has significantly increased. This leads to requirements for quality assessment, especially in video domain. Compression together with the transmission link imperfection are two main factors that influence the quality. This paper deals with the assessment of the Group of Pictures (GoP) impact on the video quality of VP9 compression standard. The evaluation was done using selected objective and subjective methods for two types of Full HD sequences depending on content. These results are part of a new model that is still being created and will be used for predicting the video quality in networks based on IP.

Modelling speech and video quality in networks based on internet protocol

A development of the tool meant to model and estimate the qualitative parameters of the speech and video transmission is the main aim of this paper. The influence of queuing techniques of individual network elements on the quality of service is explored and a model to predict this influence is created based on this information. By using this model the network administrators can successfully plan the network infrastructure with the emphasis on the communication quality, which is so important these days. The results of the model are presented using the standardised scales of mean opinion score and peak signal-to-noise ratio, which makes the results easy to understand. To complete the picture the data transmissions are explored as well making the presented tool a universal mean to predict quality of service parameters for all kinds of services.

Subjective Video Quality Assessment of H.265 Compression Standard for Full HD Resolution

Recently increasing interest in multimedia services leads to requirements for quality assessment, especially in the video domain. There are many factors that influence the video quality. Compression technology and transmission link imperfection can be considered as the main ones. This paper deals with the assessment of the impact of H.265/HEVC compression standard on the video quality using subjective metrics. The evaluation is done for two types of sequences with Full HD resolution depending on content. The paper is divided as follows. In the first part of the article, a short characteristic of the H.265/HEVC compression standard is written. In the second part, the subjective video quality methods used in our experiments are described. The last part of this article deals with the measurements and experimental results. They showed that quality of sequences coded between 5 and 7 Mbps is for observers sufficient, so there is no need for providers to use higher bitrates in streaming than this threshold. These results are part of a new model that is still being created and will be used for predicting the video quality in networks based on IP.