Video quality

About: Video quality is a research topic. Over the lifetime, 13143 publications have been published within this topic receiving 178307 citations.

Detecting fade regions in uncompressed video sequences

Abstract: The use of fade in video production to smooth scene changes and enhance the video quality complicates subsequent video compression or video editing. It is important to detect the fade regions in order to improve the quality of the compressed video or to allow automatic parsing of the video for the purpose of editing and database indexing. A fade detector that exploits the changes in the average luminosities as well as the semi-parabolic behavior of the variances of the frames in the fade region is developed. Simulation results indicate that the developed detector has over a 95% reliability rate.

Subjective evaluation of scalable video coding for content distribution

Abstract: This paper investigates the influence of the combination of the scalability parameters in scalable video coding (SVC) schemes on the subjective visual quality. We aim at providing guidelines for an adaptation strategy of SVC that can select the optimal scalability options for resource-constrained networks. Extensive subjective tests are conducted by using two different scalable video codecs and high definition contents. The results are analyzed with respect to five dimensions, namely, codec, content, spatial resolution, temporal resolution, and frame quality.

Resource Allocation for Video Streaming in Heterogeneous Cognitive Vehicular Networks

Abstract: In future fifth-generation (5G) communication systems, driven by the evolution of today's most demanding applications, video streaming over vehicle networks will play an increasingly significant role in our daily lives. In this paper, based on a heterogeneous architecture consisting of both cellular base stations (BSs) of wide coverage and cognitive-radio-enabled roadside infrastructures, a semi-Markov decision process (SMDP)-based resource-allocation scheme is proposed to facilitate video streaming application in terms of peak signal-to-noise ratio (PSNR) and smooth playback. In addition to improving video quality of vehicle users, quality of service (QoS) provisioning for background users that can originally exist in the cellular network is also considered in the proposed scheme. Specifically, based on the states of the background users, vehicle users, and the availability of the cognitive bands, the optimal resource allocation, aiming at maximizing the video streaming quality while guaranteeing the call-level performance of the background users, is achieved by addressing two interrelated joint call admission control (CAC) and channel allocation problems for cellular and roadside infrastructure networks, respectively. Simulation results show that the proposed scheme can well protect background users when coexisting with bandwidth-hungry vehicle video users and is effective in not only improving video streaming quality for vehicle users but boosting bandwidth utilization of the whole network as well.

Video Surveillance Over Wireless Sensor and Actuator Networks Using Active Cameras

Abstract: Although there has been much work focused on the camera control issue on keeping tracking a target of interest, few has been done on jointly considering the video coding, video transmission, and camera control for effective and efficient video surveillance over wireless sensor and actuator networks (WSAN). In this work, we propose a framework for real-time video surveillance with pan-tilt cameras where the video coding and transmission as well as the automated camera control are jointly optimized by taking into account the surveillance video quality requirement and the resource constraint of WSANs. The main contributions of this work are: i) an automated camera control method is developed for moving target tracking based on the received surveillance video clip in consideration of the impact of video transmission delay on camera control decision making; ii) a content-aware video coding and transmission scheme is investigated to save network node resource and maximize the received video quality under the delay constraint of moving target monitoring. Both theoretical and experimental results demonstrate the superior performance of the proposed optimization framework over existing systems.

Cross-Layer Resource Allocation for Video Streaming Over OFDMA Cognitive Radio Networks

Abstract: In this paper, a cross-layer resource allocation algorithm is proposed in the context of orthogonal frequency division multiple access (OFDMA)-based cognitive radio (CR) video application systems. User video quality and channel awareness are incorporated in the design, towards an optimal subcarrier and power allocation scheme, subject to minimum secondary receiver (SRx) video quality and primary receiver (PRx) interference threshold constraints. First, the relationship between PRx interference margin and power limits at the secondary transmitter (STx) is analytically derived. Then, to provide PRx with satisfactory quality of service (QoS), we propose a new probabilistic approach to mitigate the total imposed interference of the STx on PRx, considering imperfect STx to PRx channel state information (CSI). The effect of PRx interference limit violation probability, interference threshold, and error variance of imperfect CSI are evaluated through mathematical analysis and computer simulations. Results indicate that significant improvement in SRx total video quality is achieved through our proposed quality-aware (QA) algorithm over other state-of-the-art non-quality-aware (NQA) designs in the literature. The enhanced performance was obtained whilst guaranteeing SRx minimum quality and PRx prescribed QoS constraints.