Dependent Rate-distortion Optimization Research Articles

Pre-encoding based temporal dependent rate–distortion optimization for HEVC

Rate–distortion optimization (RDO) is a crucial technique in block-based hybrid video encoders, which determines the coding option for a certain coding unit to achieve optimal rate–distortion (R–D) performance. However, the current RDO method, which is applied in High Efficiency Video Coding (HEVC), is far from being globally optimal as it ignores the interaction among coding options. In fact, the current coding option not only determines the R–D point of the coded unit but also influences the achievable R–D​ performance of the subsequent coding units due to the spatial–temporal dependencies among the block/frame optimizations. In this paper, we first investigate the R–D characteristics, including operational R–D curves and R–D dependencies, in HEVC through several simulation experiments. It is shown that under the hierarchical fixed QP setting in the HEVC encoder, the temporal R–D dependence dominates the coding process, and the distortion of the reference frame has a strong impact on that of coded frames while less influence on rate. We then introduce distortion effect factors to quantitatively measure the temporal R–D​ dependency. The distortion effect factor at frame level reflects the correlation degree between the current coding frame and the previous coded frames, and the one at block level reflects the influence degree that the distortion of a block to that of subsequent blocks which refer to it in temporal domain. Finally, a pre-encoding based temporal dependent RDO is proposed, which adaptively adjusts quantization parameters and Lagrange multipliers according to the distortion effect factors. Experimental results show that under configurations of low-delay B and P frames, the proposed method can achieve 5.4% and 5.5% bit rate savings on average, respectively, with around 7% encoding complexity increment, compared with the original HEVC encoder.

An efficient video transcoding algorithm from h.264 to hevc

Video transcoding method usually reduces coding complexity with the cost of reducing coding efficiency. It is necessary to design a video transcoder can achieve a better trade-off between coding efficiency and complexity. This paper proposes an efficient video transcoder based on improved rate distortion optimization and improved motion vector (MV) reuse. First, we use an improved temporal dependent rate distortion optimization method to implement rate-distortion optimization (RDO) at the level of Coding Tree Units (CTUs). Second, we use improved motion vector reuse (IMVR) to reduce the complexity of encoding. Experimental results have shown that the proposed method can achieve an average reduction of 38.4% in the transcoding time with the cost of 0.6% BDBR increase compared with HEVC Test Model (HM) 16.9 encoder. It verifies that the proposed method can achieve a better trade-off between coding efficiency and complexity compared with existing transcoding methods.

Rate-Distortion Optimization Based on Two-Pass Encoding for HEVC

Rate-distortion optimization (RDO) is a crucial technique in block-based hybrid video encoders, which determines the coding option for a certain coding unit to achieve optimal rate-distortion (R-D) performance. However, the current RDO, which is implemented into High Efficiency Video Coding (HEVC) test model, i.e., HM, is far from being global optimal as it ignores the interaction among coding options. Recent studies have shown that the dependent RDO methods can improve the coding efficiency of encoders by exploring the R-D dependency among coding units, but these methods do not consider the R-D characteristics of coding units. In this paper, we proposed a two-pass encoding based RDO method, which combines both the R-D dependency and R-D characteristics, to further improve the coding efficiency. First, a frame is encoded with the original HEVC scheme to obtain the R-D model of coding tree units (CTU) and the bit budget of the frame. Second, an optimal equation combines the R-D model and R-D dependency is established to adaptively determine the Lagrange multiplier and quantization parameter (QP) for each CTU. Finally, the current frame is encoded with a new scheme again. Experimental results show that compared with the original HM, the proposed method obtains R-D performance improvements of 5.3% and 5.6% on average under configurations of low-delay B and P frames, respectively.

HEVC quantization parameter selection algorithm based on inter-frame dependency

Massive inter predictive modes are adopted in latest High Efficiency Video Coding (HEVC) standard to eliminate temporal redundancies, which results in stronger inter-frame dependency among neighboring frames than previous standards like H.264. The inter-frame dependency makes currently independent rate-distortion optimization (RDO) non-optimal any more. Quantization parameter (QP) selection algorithm taking inter-frame dependency into consideration is supposed to optimize RDO based rate control greatly. According to our research, the inter-frame dependency is reflected by the linear relationship between QP change (ΔQP) and the resulting change of distortion (ΔD). An adaptive QP selection algorithm for global RDO is proposed based on the modeling function between ΔD and ΔQP in this paper. Firstly, based on intensive statistic analysis, three parameters (initial QP ($\overline {QP}$), the length of pictures of group (GOP), and the average of SATD of one frame) are used to formulate the relationship between ΔD and ΔQP. Secondly, the resulting rate change ΔR relative to ΔQP is also formulated similarly. Thirdly, optimized Lagrangian multiplier (λ) is calculated with these two mathematic models. Finally, we refine QP values based on the optimized λ in terms of dependent RDO. The experimental results show that the proposed frame-level QP selection algorithm can decrease Bj⊘tegaard Delta BitRate (BD-BR) by about 1.62% at the random-access (RA) configuration and 1.13% at the low-delay (LD) configuration, respectively. At the same time, it doesn’t increase complexity significantly.

Distortion propagation modeling and its applications on frame level quantization control for predictive video coding

Inter-frame temporal prediction in video coding causes distortion propagation among adjacent frames. As a result, frame level bit allocation and quantization control are intrinsically to be optimized with dependent rate distortion optimization (RDO). Taking inter-frame distortion propagation into consideration, quantization parameter cascading (QPC) is an efficient technique for frame level quantization control in terms of dependent RDO. This paper proposes a temporal distortion propagation model by quantitatively evaluating the temporal distortion dependency. Block-level temporal trajectory is tracked via inter-prediction on down-sampled original frames to construct the temporal analysis chain, and then tree-style dependent analysis is implemented along the trajectory. The amounts of equivalent distortion propagated from the temporally adjacent frames are quantitatively measured. Then, a new distortion model is developed to facilitate measuring the RD (rate distortion) cost in terms of dependent RDO. Finally, a simplified trellis comprised of candidate quantization parameters (Qp) of the frames within one GOP, and the optimal Qp is searched via simplified dynamic programming to achieve global optimization. The simulation results verify that the frame level QPC algorithm achieves 3.46% BD-RATE saving on average, which is contributed by efficient bit allocation along temporal trajectory.

Inter-Block Dependency-Based CTU Level Rate Control for HEVC

Although high efficiency video coding (HEVC) has achieved high coding performance, it has been shown that dependent rate-distortion optimization (RDO) can still further improve the coding performance at the encoder side. Inspired by our previous work on temporal-dependent RDO, this paper proposes a rate control method at coding tree unit (CTU) level to obtain both higher rate-distortion (R-D) performance and lower bitrate errors. We first formulate the global optimization problem in hybrid video coding and present a general solution framework based on a weighted Lagrange multiplier, where the weighted coefficient is related to the strength of temporal dependency among coding units, and a propagation factor is introduced for quantitative measurement of the temporal dependency. Second, an estimation method of CTU level R-D model is proposed to characterize R-D relationship more accurately. Finally, under the constraint of frame level bit budget, a formulation combining inter-block dependency and R-D characteristic is developed for optimal bit allocation at the CTU level. In the process of encoding a frame, a relaxed constraint algorithm (RCA) and a strict constraint algorithm (SCA) are employed to reduce the difference between numbers of actual and target bits for the current frame, respectively. Experimental results demonstrate that, on the HEVC test model (HM-16.7), our methods including RCA and SCA achieve considerable R-D performance improvement with lower bitrate errors, outperforming the state-of-the-art schemes. It is worth mentioning that even compared with HEVC without rate control, the RCA can still achieve bitrate savings of 5.4% and 5.1% on average under configurations of low delay P and B frames, respectively.

Source Distortion Temporal Propagation Analysis for Random-Access Hierarchical Video Coding Optimization

Due to the widely used inter prediction in the current video coding standards, encoding units in different frames is of temporal dependency in that the rate-distortion optimization (RDO) of one unit may affect the coding performance of the following units in the temporal domain. To achieve optimal coding solution for a given video sequence, temporal dependency among units needs to be considered in the RDO process, which is known as the temporally dependent RDO (TD-RDO). The hierarchical coding structure (HCS) employed in the High Efficiency Video Coding (HEVC) standard further complicates this problem by grouping frames into different layers of varying coding strategies, leading to a more complex temporal relationship. In our earlier work, we addressed TD-RDO for the low delay HCS (LD-HCS), where only uni-prediction is considered. This paper aims to address more complicated TD-RDO under random access HCS (RA-HCS), where both uni-prediction and bi-prediction are considered, making the temporal relationship even more intricate. The temporal dependency introduced in the RA-HCS is thoroughly examined and an RA-based TD-RDO scheme is formulated for each layer by modeling temporal propagation of distortion under different prediction types. Based on the formulation, the global Lagrange multiplier can be obtained analytically. Moreover, the effect of random access point pictures is considered in the RA-based TD-RDO scheme. The proposed method can be simply realized by updating the Lagrange multiplier as in the independent RDO formulation or combined with adjusting quantization parameter (QP) for better results in terms of BD-rate saving. Experimental results show that under RA-HCS, the proposed method, by adapting the Lagrange multiplier only, can achieve about 2.2% bitrate savings in average. With multi-QP optimization, an average BD-rate gain of 5.2% can be obtained.

Temporally Dependent Rate-Distortion Optimization for Low-Delay Hierarchical Video Coding.

Low-delay hierarchical coding structure (LD-HCS), as one of the most important components in the latest High Efficiency Video Coding (HEVC) standard, greatly improves coding performance. It groups consecutive P/B frames into different layers and encodes them with different quantization parameters (QPs) and reference mechanisms in such a way that temporal dependency among frames can be exploited. However, due to varying characteristics of video contents, temporal dependency among coding units differs significantly from each other in the same or different layers, while a fixed LD-HCS scheme cannot take full advantage of the dependency, leading to a substantial loss in coding performance. This paper addresses the temporally dependent rate distortion optimization (RDO) problem by attempting to exploit varying temporal dependency of different units. First, the temporal relationship of different frames under the LD-HCS is examined, and hierarchical temporal propagation chains are constructed to represent the temporal dependency among coding units in different frames. Then, a hierarchical temporally dependent RDO scheme is developed specifically for the LD-HCS based on a source distortion propagation model. Experimental results show that our proposed scheme can achieve 2.5% and 2.3% BD-rate gain in average compared with the HEVC codec under the same configuration of P and B frames, respectively, with a negligible increase in encoding time. Furthermore, coupled with QP adaption, our proposed method can achieve higher coding gains, e.g., with multi-QP optimization, about 5.4% and 5.0% BD-rate saving in average over the HEVC codec under the same setting of P and B frames, respectively.

Quantization parameter cascading for video coding: leveraging a new temporal distortion propagation model

In video coder, inter-frame prediction causes distortion propagation among temporally adjacent frames. This distortion dependency is a crucial factor for rate control optimization. Quantization parameter cascading (QPC) is an efficient technique to achieve dependent rate distortion optimization (RDO). This paper proposes a general framework for temporal dependency analysis by leveraging a distortion propagation model, which is derived by employing window-based preanalysis on original frames. Then, a quantization parameter offset \(\delta \) model is proposed for achieving fine-granularity quantization control, according to the amount of distortion propagation measured by the relative propagation cost \(\rho \). This paper applies competitive decision in exploring \(\delta \)–\(\rho \) model as accurate as possible and then proposes an improved \(\delta \)–\(\rho \) model tailored for dependent RDO. The simulation results verify that the temporal QPC algorithm with the proposed model achieves up to 1.1–1.4 dB PSNR improvement, with smaller temporal distortion fluctuation contributed by efficient bit allocation.