A reduced-reference perceptual image and video quality metric based on edge preservation

In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence-prior to compression and transmission-is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. © 2012 Martini et al

Objective video quality metrics for HDTV services : a survey

The exponential growth of video traffic is expected to reach 62% of the global Internet traffic by the end of 2015. This presents as a significant challenge for the television service providers who need to employ networking technologies to monitor specific Quality of Service (QoS) parameters such as packet loss rate, jitter and delay, to ensure an acceptable level of quality. However, recent research has demonstrated that the quality experienced by the end-user does not correlate to the QoS parameters employed by most service providers. This paper investigates the correlation between the QoS parameters and the quality perceived by the end. user. These results indicate that although the QoS parameters may sometimes achieve high correlation with respect to the quality perceived by the viewer, they still have large variances. This suggests that the QoS parameters are not enough to quantify the subjective quality with a high level of confidence. This work further compares a number of existing objective video quality metrics. The results presented in this paper show that the Full-Reference Motion based Video Integrity Evaluation (MOVIE) metric and the Spatio-Temporal Reduced Reference Entropic Differences (STRRED) metric achieve excellent correlation with the subjective scores. This research also demonstrates that the STRRED metric and its derivatives have several advantages over the MOVIE metric since less information needs to be transmitted and it is less computationally intensive.peer-reviewe

A no-reference video quality metric using a natural video statistical model

The demand for high quality multimedia content is increasing rapidly, which has resulted in service providers employing Quality of Service (QoS) strategies to monitor the quality of delivered content. However, the QoS parameters commonly used do not correlate well with the actual quality perceived by the end-users. Numerous objective video quality assessment (VQA) metrics have been proposed to address this problem. However, most of these metrics rely on the availability of additional information from the original undistorted video to perform adequately, which will increase the bandwidth required. This paper presents a No-Reference (NR) VQA algorithm, which extracts a Natural Video Statistical Model using both spatial and temporal features to model the quality experienced by the end-users without needing additional information from the transmitter. These features are based on the observation that the statistics of natural scenes are regular on pristine content but are significantly altered in the presence of distortion. The proposed method achieves a Spearman Rank Order Correlation Coefficient (SROCC) of 0.8161 with subjective data, which is statistically identical and sometimes superior to existing state-of-the-art full and reduced reference VQA metrics.peer-reviewe

A reduced reference video quality assessment method for provision as a service over SDN/NFV-enabled networks

139 p.The proliferation of multimedia applications and services has generarted a noteworthy upsurge in network traffic regarding video content and has created the need for trustworthy service quality assessment methods. Currently, predominent position among the technological trends in telecommunication networkds are Network Function Virtualization (NFV), Software Defined Networking (SDN) and 5G mobile networks equipped with small cells. Additionally Video Quality Assessment (VQA) methods are a very useful tool for both content providers and network operators, to understand of how users perceive quality and this study the feasibility of potential services and adapt the network available resources to satisfy the user requirements