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Versatile video coding (VVC) aims to achieve high compression but also issues like varying content/network conditions. Existing rate control (RC) methods struggle to achieve optimal quality under these complex scenarios. This paper proposes a novel RC scheme for VVC based on a linear model. The Lagrange minimization multiplier is introduced under bit budget constraints, allowing optimized bit allocation. RC optimization is formulated as a convex solution, and is derived into the optimal quantization parameter (QP) for RC. Experimental analysis demonstrates the proposed linear model-based RC algorithm performances are better compared to other state-of-the-art methods due to their use of a linear model and optimal QP determination.

In this paper, we propose a rate control (RC) scheme for versatile video coding (VVC) to enhance coding performance. First, we propose a rate–distortion (R–D) model at the coding tree unit (CTU) level to describe the R–D relationship. Second, we adjust the quantization parameter (QP) and Lagrange multiplier at the coding unit (CU) level according to visual features to improve the rationality of local coding results. Finally, we propose a model parameter updating strategy to guarantee bitrate accuracy. The experimental results demonstrate that our RC method has better R–D performance with similar bitrate accuracy and better visual quality compared to the default RC strategy in VVC reference software VTM 10.2.

This paper concerns the analysis of important algorithmic attributes, namely, the rate of convergence and scalability, and their impact on Network Utility Maximization (NUM). The contribution of the paper is a novel distributed rate control mechanism with strong convergence and scalability properties. The proposed algorithm employs a distinctive distributed framework, where rate control is derived as a Sequential Quadratic Programming (SQP) mechanism incorporated with interior-point and trust-region methods. The NUM problem is solved by a barrier method that penalizes any violation of constraints. Lagrangian is applied to the barrier objective function, where multipliers are estimated using Least-square method to iteratively solve the quadratic approximation of the Lagrangian function at the current point to generate a search direction. The uniqueness of the algorithm is that it allows sources to estimate bandwidth prices and thereby enforces a scalable network core by pushing algorithmic complexity to the edges. The fast convergence of the algorithm, in turn, improves the responsiveness of rate control and enables reduced buffer occupancy. The convergence of the proposed algorithm is proved theoretically and is evaluated via simulations. The results demonstrate reasonable reduction of computation-time in tracking the optimal rates and validate the strong convergence properties of the proposed algorithm.

This paper presents a development of the post-compression rate-distortion optimization (PCRD-opt) algorithm in JPEG2000 used for optimal truncation (OT) rate control. The proposed treatment of PCRD-opt differs from the treatment given in the JPEG2000 standard and what is given in a number of publications. The proposed algorithm is implemented in a complete JPEG2000 compression engine as well as the algorithm published in the JPEG2000 standard. The proposed algorithm gives a substantial performance gain, outperforming the implementation given in the standard by 0.25–1 dB in PSNR on average, demonstrating an improvement from the method for PCRD-opt given in the standard.

The proposed algorithm is also compared to the JPEG2000 reference implementation, JasPer, and the popular Kakadu JPEG2000 compressor. The proposed algorithm provides equivalent performance results to both JasPer and Kakadu, indicating that the proposed PCRD-opt treatment provides correct OT of JPEG2000 compressed imagery.

Rate control plays an essential role in video coding and transmission to provide the best video quality at the receiver's end given the constraint of certain network conditions. In this paper, a rate control algorithm using the Quality Factor (QF) optimization method is proposed for the wavelet-based video codec and implemented on an open source Dirac video encoder. A mathematical model which we call Rate-QF (R - QF) model is derived to generate the optimum QF for the current coding frame according to the target bitrate. The proposed algorithm is a complete one pass process and does not require complex mathematical calculation. The process of calculating the QF is quite simple and further calculation is not required for each coded frame. The experimental results show that the proposed algorithm can control the bitrate precisely (within 1% of target bitrate in average). Moreover, the variation of bitrate over each Group of Pictures (GOPs) is lower than that of H.264. This is an advantage in preventing the buffer overflow and underflow for real-time multimedia data streaming.

Mobile video streaming is a technique that the receiver could continuously view the video content while receiving the data. An interactive framework of mobile video streaming is presented in a practical way. To reduce the effects caused by the fluctuation of wireless network, an adaptive rate control method is proposed for priority process streaming with QoS control. The transmitting data rate adapts to a suitable level according to the network status. Simulation scenario has been created to help analyse the behaviour of adaptive streaming over wireless channel. Both cases with and without the proposed method were examined and the result shows the proposed modal is able to improve the overall performance in cases when the channel conditions fluctuate.