Muhammad Arslan Usman

A No Reference Video Quality Metric Based on Jerkiness Estimation Focusing on Multiple Frame Freezing in Video Streaming

ABSTRACT In wireless networks, due to limited bandwidth and packet losses, seamless and ubiquitous delivery of high-quality video streaming services is a big challenge for the operators. In order to improve the process of online video quality monitoring, the presence of no reference (NR) objective video quality assessment (VQA) methods is required. In some networks, the video decoder on the reception side adopts a mechanism in which last correctly received frame is frozen and displayed on video display terminal until the next correct frame is received. This phenomenon, employed as an error concealment technique, can cause a perceptual jerkiness on the video display terminal. In this paper, we have proposed an enhanced model of objective VQA based on the estimation of jerkiness. A study of three contemporary NR methods, used for objective VQA and online monitoring of videos, has been included along with subjective VQA tests. The subjective tests were performed for a set of video sequences with specific spatial and temporal information. The proposed NR method is based on our careful observations from the subjective test results and our main focus is to cater the effect of multiple frame freeze impairments in video steaming. Comparison with other NR methods shows that the proposed method performs better, in terms of estimating the impact of multiple frame freezing impairments, and has more affinity with the subjective test results.

Detection of small colon bleeding in wireless capsule endoscopy videos

In the recent years, wireless capsule endoscopy (WCE) technology has played a very important role in diagnosing diseases within the gastro intestinal (GI) tract of human beings. The WCE device captures images of the GI tract of patient with a certain frame rate. Physicians examine these images in order to find abnormalities in the GI tract. This examination process is very time consuming and hectic for the physician as a WCE device captures around 60,000 images on the average. At present, there are no standards defined for the WCE image classification. Computer aided methods help reducing the burden on the physicians by automatically detecting the abnormalities in the GI tract such as small colon bleeding. In this paper, a pixel based approach to detect bleeding regions in the WCE videos by using a support vector classifier is proposed. Threshold analysis in HSV color space is performed to compute the features for training an optimal support vector machine. The HSV features of the WCE images are fed to the trained support vector classifier for classification. Also, our method includes image enhancement and edge removal in WCE images, which is done prior to classification, for robust results. The method offers high sensitivity, specificity and accuracy in terms of correctly classifying images that contain bleeding regions as compared to another contemporary method. A detailed experimental analysis is also provided for the purpose of method evaluation.

Bandwidth Adaptation by Squeezing Idle Traffic in Browsers: An Active Window Detection Based Approach for Next Generation Networks

This letter proposes a novel algorithm named bandwidth adaptation by squeezing idle traffic (BASIT), which aims at reducing the video traffic in idle tabs/windows of browsers. The algorithm is based on detecting active tabs/windows in the browsers at client end. Video data on idle tabs are intelligently compressed by the server to save network bandwidth. Bandwidth wasted on idle video traffic is reduced by either sending the lowest quality of the video or only audio throughout the idle duration of the tabs/windows. It is understandable that substantial amount of bandwidth can be saved by applying BASIT algorithm on browsers.

A no reference method for detection of dropped video frames in live video streaming

This paper presents a no reference method for efficient detection of dropped video frames in live video streaming. Temporal information of video frames is calculated and is used to detect dropped video frames. The videos are analyzed in binary form instead of true color format RGB in order to reduce the computational time. The proposed method uses two separate thresholds for videos containing high and low motion content. The temporal information of videos is examined using the defined thresholds and then results are combined to calculate the total number of dropped frames. According to the existing literature, no reference methods are unable to correctly perceive low motion content in video frames and falsely classify them as dropped or frozen frames. Our method overcomes this problem as it uses separate thresholds for high and low motion content. Furthermore, as our method uses video frames in binary format, so it offers low computational time as compared to other contemporary methods. The simulation results and comparison show that our method offers high accuracy with low computation time.

On the performance of perfect and imperfect SIC in downlink non orthogonal multiple access (NOMA)

Non orthogonal multiple access (NOMA) is a new radio access technique considered to be a possible candidate for 5G and beyond. Recent studies confirm that it provides better performance gains as compared to the orthogonal multiple access (OAM) techniques currently in use. This paper investigates the performance of downlink NOMA using the ideal and non-ideal successive interference cancellation (SIC) conditions. The ideal and non-ideal SIC conditions are referred as perfect and imperfect SIC respectively in this study. The purpose of this study is to provide a more realistic analysis of SIC in downlink NOMA rather than considering the perfect SIC conditions. Simulation results are provided at the end of the paper in terms of bit error rate (BER) at the receiver end using both perfect and imperfect SIC.

Swapped Huffman tree coding application for low-power wide-area network (LPWAN)

Data compression and encryption play key role in the modern wireless communication technologies, especially, in internet of things (IoT). Main problems with successful implementation of IoT are; the use of low power long range devices and the requirement of managing huge amount of data; mainly, compression and security of the data transfer. In this work, to cope with these issues, we have applied swapped Huffman tree (SHT) coding to a low power wide-area network (LPWAN) for realizing its benefits. The applied SHT coding compresses and encodes the data at the same time which is clearly shown in this work with the help of examples. Performance evaluation is shown at the end of the paper.

Performance Analysis of a No-Reference Temporal Quality Assessment Metric for Videos Impaired by Frame Freezing Artefacts

 Abstract—In This paper, a temporal video quality assessment metric has been studied and evaluated on the basis of its ability to detect frozen video frames in a digitally transmitted video sequence and assess the quality accordingly. The metric is a temporal quality method that is centered around measuring the annoyance of frame freeze duration. This metric uses mean square difference (MSD) value between video frames to mark freeze events and builds a mapping function based on such durations of freeze to estimate the objectivemean opinion score (MOS). Two test scenarios have been designed for the analysis, Single freeze and multiple freeze experiment, keeping in view the recommendations of international telecommunication union (ITU). The analysis has been done with the help of MATLAB simulations and finally some limitations of the temporal quality metric are shown at the end of the paper.

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.

Channel resource allocation and availability prediction in hybrid access femtocells

Abstract In this paper, three channel assignment models are proposed for channel resource allocation in femtocells. The models proposed are based on the Markov chain process. According to the access mechanisms in femtocells, the Third-Generation Partnership Project (3GPP) has described two kinds of users in the femtocell application; open users and the closed subscriber group (CSG). In hybrid access mechanism for femtocells, both CSG users and open users are usually referred as subscribers and non-subscribers respectively. So, in this work, for all the proposed models, the CSG and open users are categorized into two groups; the subscriber group (SG) and the non-subscriber group (NSG) respectively. The proposed models provide priority based channel resource allocation strategies between the SG and NSG. Furthermore, the focus of this research is to provide variable channel resource sharing among the SG and NSG to keep the wastage of channel resources minimum for better quality of service (QoS). The analysis is conducted in terms of channel resource blocking management for all the models and to validate the analysis, simulations are performed at the end of this paper. Further, channel resource blocking prediction, based on the blocking probability results for SG and NSG users, is also provided at the end. The prediction is done through risk analysis using the @ Risk tool. The simulations are provided in two parts; 1) the probability curves for SG and NSG against the total number of channels and 2) the risk analysis results for blocked channels prediction using the @ Risk tool.

Quality assessment for wireless capsule endoscopy videos compressed via HEVC

Maintaining the quality of medical images and videos is an essential part of the e-services provided by the healthcare sector. The convergence of modern communication systems and the healthcare industry necessitates the provision of better quality of service and experience by the service provider. Recent inclusion and standardization of the high efficiency video coder (HEVC) has made it possible for medical data to be compressed and transmitted over wireless networks with minimal compromise of the quality. Quality evaluation and assessment of these medical videos transmitted over wireless networks is another important research area that requires further exploration and attention. In this paper, we have conducted an in-depth study of video quality assessment for compressed wireless capsule endoscopy (WCE) videos. Our study includes the performance evaluation of several state-of-the-art objective video quality metrics in terms of determining the quality of compressed WCE videos. Subjective video quality experiments were conducted with the assistance of experts and non-experts in order to predict the diagnostic and visual quality of these medical videos, respectively. The evaluation of the metrics is based on three major performance metrics that include, correlation between the subjective and objective scores, relative statistical performance and computation time. Results show that the metrics information fidelity criterion (IFC), visual information fidelity-(VIF) and especially pixel based VIF stand out as best performing metrics. Furthermore, our paper reports the performance of HEVC compression on medical videos and according to the results, it performs optimally in preserving the diagnostic and visual quality of WCE videos at Quantization Parameter (QP) values of up to 35 and 37 respectively.