Video quality

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

Intelligent frame skipping in video coding based on similarity metric in compressed domain

Abstract: This disclosure provides intelligent frame skipping techniques that may be used by an encoding device or a decoding device to facilitate frame skipping in a manner that may help to minimize quality degradation due to the frame skipping. In particular, the described techniques may implement a similarity metric designed to identify good candidate frames for frame skipping. In this manner, noticeable reductions in the video quality caused by frame skipping, as perceived by a viewer of the video sequence, may be reduced relative to conventional frame skipping techniques. The described techniques advantageously operate in a compressed domain.

Low-Complexity Video Quality Assessment Using Temporal Quality Variations

Abstract: Objective video quality assessment (VQA) is the use of computational models to evaluate the video quality in line with the perception of the human visual system (HVS). It is challenging due to the underlying complexity, and the relatively limited understanding of the HVS and its intricate mechanisms. There are three important issues that arise in objective VQA in comparison with image quality assessment: 1) the temporal factors apart from the spatial ones also need to be considered, 2) the contribution of each factor (spatial and temporal) and their interaction to the overall video quality need to be determined, and 3) the computational complexity of the resultant method. In this paper, we seek to tackle the first issue by utilizing the worst case pooling strategy and the variations of spatial quality along the temporal axis with proper analysis and justification. The second issue is addressed by the use of machine learning; we believe this to be more convincing since the relationship between the factors and the overall quality is derived via training with substantial ground truth (i.e., subjective scores). Experiments conducted using publicly available video databases show the effectiveness of the proposed full-reference (FR) algorithm in comparison to the relevant existing VQA schemes. Focus has also been placed on demonstrating the robustness of the proposed method to new and untrained data. To that end, cross-database tests have been carried out to provide a proper perspective of the performance of proposed scheme as compared to other VQA methods. The third issue regarding the computational costs also plays a key role in determining the feasibility of a VQA scheme for practical deployment given the large amount of data that needs to be processed/analyzed in real time. A limitation of many existing VQA algorithms is their higher computational complexity. In contrast, the proposed scheme is more efficient due to its low complexity without jeopardizing the prediction accuracy.

Optimization of HTTP adaptive streaming over mobile cellular networks

Abstract: Video streaming, in particular, hypertext transfer protocol based (HTTP) adaptive streaming (HAS) of video, is expected to be a dominant application over mobile networks in the near future. The observation that the base station can alter the video quality requested by a HAS client to its server by controlling the over-the-air throughput from the base station to the client implies that the base station can jointly maximize aggregate video quality of all the HAS flows and throughput of data flows that it serves. We formulate a utility maximization problem that separately takes into account different utility functions for video and data flows and show that the utility maximization can be achieved through an algorithm, we term adaptive guaranteed bit rate (AGBR), wherein target bit rates are calculated for each HAS flow and passed on to an underlying minimum rate proportional fair scheduler that schedules resources across all the flows. This approach has the advantage that it retains the existing scheduling function in the base station with a separate function to compute the target bit rates for the video flows allowing them to only change slowly over time in order to avoid frequent video quality changes. Through analytical modeling and simulations we show that the proposed algorithm can achieve required fairness among the video flows as well as automatically and fairly adapt video quality with increasing congestion thereby preventing data flow throughput starvation.

Low-Delay Rate Control for Consistent Quality Using Distortion-Based Lagrange Multiplier

Abstract: Video quality fluctuation plays a significant role in human visual perception, and hence, many rate control approaches have been widely developed to maintain consistent quality for video communication. This paper presents a novel rate control framework based on the Lagrange multiplier in high-efficiency video coding. With the assumption of constant quality control, a new relationship between the distortion and the Lagrange multiplier is established. Based on the proposed distortion model and buffer status, we obtain a computationally feasible solution to the problem of minimizing the distortion variation across video frames at the coding tree unit level. Extensive simulation results show that our method outperforms the rate control used in HEVC Test Model (HM) by providing a more accurate rate regulation, lower video quality fluctuation, and stabler buffer fullness. The average peak signal-to-noise ratio (PSNR) and PSNR deviation improvements are about 0.37 dB and 57.14% in the low-delay (P and B) video communication, where the complexity overhead is $\sim 4.44\%$ .