Consistent Video Quality Research Articles

A New Blind Video Quality Metric for Assessing Different Turbulence Mitigation Algorithms

Although many algorithms have been proposed to mitigate air turbulence in optical videos, there do not seem to be consistent blind video quality assessment metrics that can reliably assess different approaches. Blind video quality assessment metrics are necessary because many videos containing air turbulence do not have ground truth. In this paper, a simple and intuitive blind video quality assessment metric is proposed. This metric can reliably and consistently assess various turbulent mitigation algorithms for optical videos. Experimental results using more than 10 videos in the literature show that the proposed metrics correlate well with human subjective evaluations. Compared with an existing blind video metric and two other blind image quality metrics, the proposed metrics performed consistently better.

Adaptive Reservation of Network Resources According to Video Classification Scenes.

Video quality evaluation needs a combined approach that includes subjective and objective metrics, testing, and monitoring of the network. This paper deals with the novel approach of mapping quality of service (QoS) to quality of experience (QoE) using QoE metrics to determine user satisfaction limits, and applying QoS tools to provide the minimum QoE expected by users. Our aim was to connect objective estimations of video quality with the subjective estimations. A comprehensive tool for the estimation of the subjective evaluation is proposed. This new idea is based on the evaluation and marking of video sequences using the sentinel flag derived from spatial information (SI) and temporal information (TI) in individual video frames. The authors of this paper created a video database for quality evaluation, and derived SI and TI from each video sequence for classifying the scenes. Video scenes from the database were evaluated by objective and subjective assessment. Based on the results, a new model for prediction of subjective quality is defined and presented in this paper. This quality is predicted using an artificial neural network based on the objective evaluation and the type of video sequences defined by qualitative parameters such as resolution, compression standard, and bitstream. Furthermore, the authors created an optimum mapping function to define the threshold for the variable bitrate setting based on the flag in the video, determining the type of scene in the proposed model. This function allows one to allocate a bitrate dynamically for a particular segment of the scene and maintains the desired quality. Our proposed model can help video service providers with the increasing the comfort of the end users. The variable bitstream ensures consistent video quality and customer satisfaction, while network resources are used effectively. The proposed model can also predict the appropriate bitrate based on the required quality of video sequences, defined using either objective or subjective assessment.

A Novel Consistent Quality Driven for JEM Based Distributed Video Coding

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.

Adaptive Bit Allocation for Consistent Video Quality in Scalable High Efficiency Video Coding

Scalable video coding (SVC) is a coding paradigm that allows once-encoded video content to be used in diverse scenarios. SVC-coded videos can be transmitted and rendered at specified bitrates according to network bandwidth and end device requirements. In this paper, an adaptive bit allocation algorithm is proposed for the emerging scalable High Efficiency Video Coding (SHVC) standard. The bit budget at the group-of-pictures level is allocated according to buffer occupancy. Picture complexity, measured using the predicted mean absolute difference (MAD), buffer occupancy, and hierarchical level, is proposed for regulating the bitrate at the picture level. The MAD of the current picture is predicted using a novel mean prediction error (MPE) model, which is obtained from the advanced motion vector prediction, and the test zone search specified in SHVC and the associated reference software of SHVC. Moreover, MPE is used to determine the number of assigned bits at the coding-tree-unit level. The bit budget of each level is incorporated with the $R-\lambda $ model for computing the required quantization parameter. Experimental results reveal that the proposed method achieves accurate bitrates with enhanced and consistent visual quality and more satisfactorily controls buffer occupancy compared with the state-of-the-art approaches reported in the literature.

A Content-Aware Video Encoding Scheme Based on Single-Pass Consistent Quality Control

In real-time video streaming applications based on battery-powered camera systems, it is crucial to capture and transmit critical information satisfying the storage capacity and channel bandwidth requirement. In this paper, we propose a single-pass content-aware video encoding scheme for such applications to achieve a consistent video quality while satisfying the bit-rate constraints. To achieve the objective we developed: 1) scene descriptor based on the discrete cosine transformation coefficients obtained from the video encoder; 2) a parameterized analytic distortion model for video encoding using the scene descriptor; 3) scene change detection based on the encoded MB mode ratio; and 4) a single-pass consistent video quality control scheme which exploits 1), 2), and 3). Experimental results show that the proposed method results in less deviation from the target distortion and less distortion variance than the up-to-date best result by up to 65.25% and 75.88%, respectively, while satisfying the given rate constraints. The computing time overhead in the proposed method was 0.560% and 0.571% for the variable and constrained variable bit-rate mode, respectively, which is negligible in nearly all embedded applications.

An Efficient Frame-Level Rate Control Algorithm for High Efficiency Video Coding

In video coding, the goal of rate control (RC) is not only to avoid the undesirable fluctuation in bit allocation, but also to provide a good visual perception. In this paper, a novel frame-level rate control algorithm for High Efficiency Video Coding (HEVC) is proposed. Firstly a model that reveals the relationship between bit per pixel (bpp), the bitrate of the intra frame and the bitrate of the subsequent inter frames in a group of pictures (GOP) is established, based on which the target bitrate of the first intra frame is well estimated. Then a novel frame-level bit allocation algorithm is developed, which provides a robust bit balancing scheme between the intra frame and the inter frames in a GOP to achieve the visual quality smoothness throughout the whole sequence. Our experimental results show that when compared to the RC scheme for HEVC encoder HM-16.0, the proposed algorithm can produce reconstructed frames with more consistent objective video quality. In addition, the objective visual quality of the reconstructed frames can be improved with less bitrate.

Window-based rate control for video quality optimization with a novel INTER-dependent rate-distortion model

Most model-based rate control schemes use independent rate-distortion (R–D) models at macroblock (MB) level to represent the relationship among bit rate, distortion and encoding complexity. However the correlations between frames (INTER-dependency) are not well considered for distortion, bit allocation and quantization parameter (QP) decision. In this paper, a novel INTER-dependent R–D model is proposed based on the theoretical analysis of the relationship between the predicted residual of one frame and the distortion of its reference frame. To achieve both bit rate accuracy and consistent video quality, a window-based rate control scheme with two sliding windows is introduced. One window is to group certain previously encoded frames and current frame to control the bit rate and buffer delay; the other is to group certain future encoding frames to optimize the fluctuation of video quality. Furthermore, the optimization of Lagrange multiplier is also discussed under the INTER-dependent situation. Experimental results demonstrate that the proposed window-based rate control scheme with INTER-dependent R–D model can achieve accurate target bit rate and improve PSNR performance, meanwhile the variation of PSNR is the smallest compared with other three benchmark algorithms. This one-pass rate control scheme is highly practical for the real-time video coding applications.

Consistent Video Quality Control in Scalable Video Coding Using Dependent Distortion Quantization Model

Consistent video quality control is an important and practical issue for video streaming applications. Several algorithms have been developed in the literature that aims to maintain consistent quality through the entire video sequence, whereas most of them focus on non-scalable video coding. In this paper, we propose an algorithm for consistent quality control for H.264/AVC based scalable video coding (SVC), relying on a dependent distortion-quantization (D-Q) model. Such a dependent D-Q model is developed to capture the distortion behavior of frames at enhancement layers (ELs) by exploring the correlation between two successive layers. Experimental results demonstrate that the proposed model can accurately estimate the distortion of each frame at different layers in the quality, temporal, and spatial scalability. The proposed model is applied in SVC where the quantization parameter of each frame at EL is carefully selected to achieve consistent video quality given the distortion constraint. Meanwhile, model parameters are initialized using the content features extracted from the underlying video sequences, and updated using the encoded data at the frame level. Simulations show that the proposed scheme enables more stable video quality with the PSNR keeping close to the target value (i.e., small PSNR variation).

H.264/SVC parameter optimization based on quantization parameter, MGS fragmentation, and user bandwidth distribution

In the situation of limited bandwidth, how to improve the performance of scalable video coding plays an important role in video coding. The previously proposed scalable video coding optimization schemes concentrate on reducing coding computation or trying to achieve consistent video quality; however, the connections between coding scheme, transmission environments, and users’ accesses manner were not jointly considered. This article proposes a H.264/SVC (scalable video codec) parameter optimization scheme, which attempt to make full use of limited bandwidth, to achieve better peak signal-to-noise ratio, based on the joint measure of user bandwidth range and probability density distribution. This algorithm constructs a relationship map which consists of the bandwidth range of multiple users and the quantified quality increments measure, QP e , in order to make effective use of the video coding bit-stream. A medium grain scalability fragmentation optimization algorithm is also presented with respect to user bandwidth probability density distribution, encoding bit rate, and scalability. Experiments on a public dataset show that this method provides significant average quality improvement for streaming video applications.

Rate Control Scheme for Consistent Video Quality in Scalable Video Codec

Multimedia data delivered to mobile devices over wireless channels or the Internet are complicated by bandwidth fluctuation and the variety of mobile devices. Scalable video coding has been developed as an extension of H.264/AVC to solve this problem. Since scalable video codec provides various scalabilities to adapt the bitstream for the channel conditions and terminal types, scalable codec is one of the useful codecs for wired or wireless multimedia communication systems, such as IPTV and streaming services. In such scalable multimedia communication systems, video quality fluctuation degrades the visual perception significantly. It is important to efficiently use the target bits in order to maintain a consistent video quality or achieve a small distortion variation throughout the whole video sequence. The scheme proposed in this paper provides a useful function to control video quality in applications supporting scalability, whereas conventional schemes have been proposed to control video quality in the H.264 and MPEG-4 systems. The proposed algorithm decides the quantization parameter of the enhancement layer to maintain a consistent video quality throughout the entire sequence. The video quality of the enhancement layer is controlled based on a closed-form formula which utilizes the residual data and quantization error of the base layer. The simulation results show that the proposed algorithm controls the frame quality of the enhancement layer in a simple operation, where the parameter decision algorithm is applied to each frame.

VBR rate control for perceptually consistent video quality

In contrast with traditional VBR control strategies, such as constant QP and constant PSNR, we take the characteristics of human visual system into account and propose a two-pass VBR rate control for perceptually consistent video quality, mainly for DVD like video storage applications. We employ spatial-temporal complexity to evaluate the subjective visual quality and propose a statistical quality relation between the Qstep and complexity. We further extend it to a RDO based practical Q-Complexity model to effectively guide our second-pass VBR encoding. In addition, we adopt a fast iterative search technique and a run-time bit production control mechanism to satisfy the constraint of fixed storage capacity while producing consistent perceived quality. Our experimental results from various test clips have demonstrated its efficiency and reliability, indicating a noticeable improvement on video quality.

Efficient Rate Control Scheme Using Complexity of Macro Block for MPEG-2 Transcoder

When the bit rate of a compressed video sequence is reduced by a frequency domain transcoder system, the rate control scheme plays a very important role in maintaining consistent video quality. In this paper, we propose an efficient rate control scheme based on the complexity of MB (Macro Block) while conventional transcoding schemes use that of a picture. Since the frequency domain transcoder has to calculate the spatial activity of MB to adjust the quantization step, a process of converting the DCT (Discrete Cosine Transform) data into spatial one is required. The proposed scheme calculates the spatial activity from DCT data without converting them to pixel domain.

Reducing video-quality fluctuations for streaming scalable video using unequal error protection, retransmission, and interleaving

Forward error correction based multiple description (MD-FEC) transcoding for transmitting embedded bitstream over the packet erasure networks has been extensively studied in the past. In the existing work, a single embedded source bitstream, e.g., the bitstream of a group of pictures (GOP) encoded using three-dimensional set partitioning in hierarchical trees is optimally protected unequal error protection (UEP) in the rate-distortion sense. However, most of the previous work on transmitting embedded video using MD-FEC assumed that one GOP is transmitted only once, and did not consider the chance of retransmission. This may lead to noticeable video quality variations due to varying channel conditions. In this paper, a novel window-based packetization scheme is proposed, which combats bursty packet loss by combining the following three techniques: UEP, retransmission, and GOP-level interleaving. In particular, two retransmission mechanisms, namely segment-wise retransmission and byte-wise retransmission, are proposed based on different types of receiver feedback. Moreover, two levels of rate allocations are introduced: intra-GOP rate allocation minimizes the distortion of individual GOP; while inter-GOP rate allocation intends to reduce video quality fluctuations by adaptively allocating bandwidth according to video signal characteristics and client buffer status. In this way, more consistent video quality can be achieved under various packet loss probabilities, as demonstrated by our experimental results.

Optimal quality adaptation for scalable encoded video

The dynamic behavior of the Internet's transmission resources makes it difficult to provide perceptually good quality streaming video. Scalable video encoding techniques have been proposed to deal with this problem. However, an encoded video generally exhibits significant data rate variability to provide consistent visual quality. We are, therefore, faced with the problem of accommodating the mismatch between the available bandwidth variability and the encoded video variability. We investigate quality adaptation algorithms for scalable encoded variable bit-rate video over the Internet. Our goal is to develop a quality adaptation scheme that maximizes perceptual video quality by minimizing quality variation, while at the same time increasing the usage of available bandwidth. We propose an optimal adaptation algorithm and a real-time adaptation algorithm based on whether the network conditions are known a priori. Experimental results show that the real-time adaptation as well as the optimal adaptation algorithm provide consistent video quality when used over both TCP-friendly rate control (TFRC) and transmission control protocol (TCP).

Rate–distortion model based rate control for real-time VBR video coding and low-delay communications

Abstract Rate control is an important component in a video encoder for data storage or real-time visual communications. In the paper, we will discuss the rate control in MPEG encoder for low-delay real-time video communications over variable bit-rate (VBR) channel. In low-delay video communications, the video transmission is subject not only to the channel rate constraints, but also to the end-to-end delay constraints. In the paper, we employ leaky-bucket model to describe the traffic parameters and monitor the encoder's output. First, an ad hoc bit-allocation method is introduced. Although satisfying the rate constraints perfectly, it provides the objective quality of the decoded image to be just comparable to that of CBR rate control using MPEG2 TM5. Then, a new rate–distortion model is developed, based on which an advanced rate control algorithm is designed, producing almost uniform distortion within a frame as well as consistent video quality between frames. Experimental results show that, when compared to both the MPEG2 TM5 and the proposed ad hoc bit-allocation method, the advanced rate control algorithm maintains not only a constant buffer delay, but also a stable decoded image quality in the scenario of VBR transmission.

Rate control for VBR video over ATM: simplification and implementation

Rate control is essential to ensure high-quality video transmission over asynchronous transfer mode (ATM) networks; both source and channel rates must not violate buffer or network traffic constraints in order to guarantee decoded video quality. To date, source and channel rate selection has been performed jointly because the rates are related through buffer and network constraints and therefore appear to be interdependent. It is shown that selection of these rates can be separated and the rate control problem is therefore simplified, allowing sequential source and channel rate selection without the need for iteration. A rate control algorithm is proposed which implements noniterative, separate sequential selection of source and channel rates in order to minimize the distortion variation between frames, subject to all buffer and network constraints. In particular, the leaky bucket is used as the traffic policing mechanism. Achieving a target rate for individual frames is facilitated by using a rate-distortion optimized video coder which allows coding to an exactly specified rate or distortion. Channel rate selection is performed following source rate selection with the goal of providing smooth traffic to the network, thereby allowing a high statistical multiplexing gain. Experiments demonstrate that the proposed noniterative rate control algorithm, when implemented using the optimized coder, achieves consistent video quality while providing smooth traffic to the network.

A survey of statistical source models for variable-bit-rate compressed video

It is predicted that, in the near future, the transport of compressed video will pervade computer networks. Variable-bit-rate (VBR) encoded video is expected to become a significant source of network traffic, due to its advantages in statistical multiplexing gain and consistent video quality. Both systems analysts and developers need to assess and study the impact these sources will have on their networks and networking products. To this end, suitable statistical source models are required to analyze performance metrics such as packet loss, delay and jitter. This paper provides a survey of VBR source models which can be used to drive network simulations. The models are categorized into four groups: Markov chain/linear regression, TES, self-similar and i.i.d/analytical. We present models which have been used for VBR sources containing moderate-to-significant scene changes and moderate-to-full motion. A description of each model is given along with corresponding advantages and shortcomings. Comparisons are made based on the complexity of each model.

Video transcoding architecture with minimum buffer requirement for compressed MPEG-2 bitstream

In this paper, an extremely efficient MPEG-2 video transcoding method is proposed, which has a low buffer requirement and results in low delay. Most importantly, the proposed method does not need the computational intensive motion estimation. Simulation results demonstrate that the proposed approach results in very consistent video quality and maintains the buffer level effectively. Compared with direct decode/encode approach, the proposed approach only suffers slight quality degradation.

Joint encoder and channel rate control of VBR video over ATM networks

Rate control is considered an important issue in video coding, since it significantly affects video quality. We discuss joint encoder and channel rate control for variable bit-rate (VBR) video over packet-switched ATM networks. Since variable bit-rate traffic is allowed in such networks, an open-loop encoder without rate control can generate consistent quality video. However, in order to improve the statistical multiplexing gain (SMG), an encoder buffer is essential to meet traffic constraints imposed by networks and to smooth the highly variable video bitstream. Due to the finite buffer size, some forms of encoder rate control have to be enforced, and consequently, video quality varies. We argue that a rate control scheme has to balance both issues of consistent video quality on the encoder side and bitstream smoothness for the SMG on the network side. We present a joint encoder and channel rate control algorithm for ATM networks with leaky buckets as open-loop source flow control models. The algorithm considers constraints imposed by the encoder and decoder buffers, the leaky bucket control, traffic smoothing, and rate control. The encoder rate control is separated into a sustainable-rate control and a unidirectional instantaneous-rate control. It can improve the problem of leaky bucket saturation exhibited in previous works. Experimental results with MPEG video are presented. The results verify our analysis and show the effectiveness of the proposed algorithm.

多重読取り可能なビデオオンデマンドシステム

Digital video-on-demand is becoming important, in conjunction with the digitazation of communications and advances in video compression techniques. This paper proposes three new techniques to improve the function and performance of digital video-on-demand systems : multiple readouts of video programs within a few seconds from a disk drive, variable-bit-rate video storage for consistent video quality and efficient multiple readouts, and audio-and-video synchronization that is compatible with a variety of communication networks and video decoding speeds. A new system architecture is also proposed to employ these techniques and video packet transmission. The feasibility of these techniques is experimentally verified. A response time of under one second is achieved from a program request to program initiation on a terminal. In addition, simultaneous access to a video storage server is possible from four terminals if the maximum video bit rate is 2.8 Mbps.