Studying Rate Control Methods for UHDTV Delivery Using HEVC

Since the early video coding standardisation efforts, rate control has been considered essential for almost any application, and has therefore been extensively studied. With the advent of improved video coding standards, such as the current stateof-the-art High Efficiency Video Coding (HEVC) standard, and the introduction of advanced flexible coding tools, previous Rate-Distortion (RD) models used for rate control have become obsolete. To address this issue, some rate control methods have been recently proposed specifically for HEVC which introduce many useful features, such as a robust correspondence between the rate and Lagrange multiplier . However, when applying these rate control methods on sequences in the new Ultra High Definition Television (UHDTV) format, degraded coding performance was observed. In this paper, an analysis of the state-of-the-art HEVC rate control method was performed and two directions for its improvement were evaluated. These improvements target frame-level bit-allocation and model parameter initialisation. When compared to the rate control method implemented in the HEVC reference software, these improvements result in reduced BDrate losses of 3:1% and 2:1%, versus the 8:8% provided by the reference algorithm. Moreover, the proposed improvements improve the accuracy in hitting the target bit-rate./p

A rate control algorithm for HEVC with hierarchical GOP structures

In this paper a buffer-constrained rate control (RC) algorithm for High Efficiency Video Coding (HEVC) with hierarchical group of pictures structures is proposed. Specifically, a quantization parameter (QP) cascading approach, which the QP value is increased from one temporal layer to the next, is employed to achieve high coding efficiency while maintaining the buffer fullness at secure levels. When compared to the current state-of-the-art RC algorithm, the experimental results show that our proposal achieves a slightly better rate-distortion performance and a remarkably better buffer control with an acceptable increase in computational complexity

Bit Allocation using Optimization

In this paper, we consider the problem of bit allocation in neural video compression (NVC). Due to the frame reference structure, current NVC methods using the same R-D (Rate-Distortion) trade-off parameter $\lambda$ for all frames are suboptimal, which brings the need for bit allocation. Unlike previous methods based on heuristic and empirical R-D models, we propose to solve this problem by gradient-based optimization. Specifically, we first propose a continuous bit implementation method based on Semi-Amortized Variational Inference (SAVI). Then, we propose a pixel-level implicit bit allocation method using iterative optimization by changing the SAVI target. Moreover, we derive the precise R-D model based on the differentiable trait of NVC. And we show the optimality of our method by proofing its equivalence to the bit allocation with precise R-D model. Experimental results show that our approach significantly improves NVC methods and outperforms existing bit allocation methods. Our approach is plug-and-play for all differentiable NVC methods, and it can be directly adopted on existing pre-trained models

Region-of-interest based rate control scheme for high efficiency video coding

International audienceIn this paper, we propose a new rate control scheme designed for the newest high efficiency video coding (HEVC) standard, and aimed at enhancing the quality of regions of interest (ROI). Our approach allocates a higher bit rate to the region of interest while keeping the global bit rate close to the assigned target value. This algorithm is developed for a videoconferencing system, where the ROIs (typically, faces) are automatically detected and each coding unit is classified in a region of the interest map. This map is given as input to the rate control algorithm and the bit allocation is made accordingly. Experimental results show that the proposed scheme achieves accurate target bit rates and provides an improvement in the region of interest quality, both in objective metrics and based on subjective quality evaluation

Optimized Data Representation for Interactive Multiview Navigation

In contrary to traditional media streaming services where a unique media content is delivered to different users, interactive multiview navigation applications enable users to choose their own viewpoints and freely navigate in a 3-D scene. The interactivity brings new challenges in addition to the classical rate-distortion trade-off, which considers only the compression performance and viewing quality. On the one hand, interactivity necessitates sufficient viewpoints for richer navigation; on the other hand, it requires to provide low bandwidth and delay costs for smooth navigation during view transitions. In this paper, we formally describe the novel trade-offs posed by the navigation interactivity and classical rate-distortion criterion. Based on an original formulation, we look for the optimal design of the data representation by introducing novel rate and distortion models and practical solving algorithms. Experiments show that the proposed data representation method outperforms the baseline solution by providing lower resource consumptions and higher visual quality in all navigation configurations, which certainly confirms the potential of the proposed data representation in practical interactive navigation systems