Quantization Parameter Determination Research Articles

A Rate Control Scheme for VVC Intercoding Using a Linear Model

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.

Learning From Coding Features: High Efficiency Rate Control for AOMedia Video 1

Rate control, which typically includes bit allocation and quantization parameter (QP) determination, plays an important role in real-world video coding applications. In this paper, we propose a novel rate control scheme for AOMedia Video 1 (AV1) which enjoys adaptive bit allocation and effective QP determination. In particular, two supporting vector regression (SVR) models are learned for the hierarchical bit allocation and frame-level parameter estimation. To train the models, the multi-pass coding strategy is utilized for training data acquisition. Compared to the default scheme in AV1 and the state-of-the-art method, the proposed rate control scheme achieves superior performance in terms of bitrate accuracy and coding efficiency.

Adaptive bit allocation scheme for rate control in high efficiency video coding with initial quantization parameter determination

One of the challenges in rate control (RC) lies in how to efficiently determine a target bit rate that will be used for the quantization parameter (Qp) calculation process during video coding. In this paper, we investigate the issues over the existing bit allocation algorithms for the RC process in High Efficiency Video Coding (HEVC) and propose an complexity-based bit allocation scheme to improve the encoding performance. First, we model the relationship between encoding bit rate and texture complexity by a linear rate function. Second, compared with traditional complexity estimation methods, a more accurate model is proposed to measure the texture complexity considering the spatial–temporal correlations. Third, based on the proposed rate function and texture complexity measurement model, we develop an adaptive bit allocation scheme for RC in HEVC. At the same time, depending on the encoder buffer status, an adaptive Qp clip range determination algorithm is also developed to achieve the encoding quality smoothness while keeping the bit rate fluctuation at an acceptable level. Then, we exploit to determine the initial Qp efficiently and adaptively according to video contents. Experimental results demonstrate that the proposed RC algorithm can achieve better rate-distortion (R–D) and rate-control performance than that of the state-of-the-art RC scheme implemented in the HEVC reference software HM11.0.

Attentional mechanisms driven adaptive quantization and selective bit allocation scheme for H.264/AVC

Rate control algorithm adopted in H.264/AVC reference software shows several shortcomings that have been highlighted by different studies. For instance, in the baseline profile, the frame target bit-rate estimation assumes similar characteristics for all frames and the quantization parameter determination uses the Mean Absolute Difference for complexity estimation. Consequently, an inefficient bit allocation is performed leading to important quality variation of decoded sequences. A saliency-based rate-control is proposed in this paper to achieve bit-rate saving and improve perceived quality. The saliency map of each frame, simulating the human visual attention by a bottom-up approach, is used at the frame level to adjust the quantization parameter and at the macroblock level to guide the bit allocation process. Simulation results show that the proposed attentional model is well correlated to human behavior. When compared to JM15.0 reference software, at the frame level, the saliency map exploitation achieves bit-rate savings of up to 26%. At the MB level and under the same quality constraint, bit-rate improvement is up to 42% and buffer level variation is reduced by up to 71%.

PSNR-based Initial QP Determination for Low Bit Rate Video Coding

In H.264/AVC, the first frame of a group of pictures (GOP) is encoded in intra mode which generates a large number of bits. The number of bits for the I-frame affects the qualities of the following frames of a GOP since they are encoded using the bits remaining among the bits allocated to the GOP. In addition, the first frame is used for the inter mode encoding of the following frames. Thus, the initial quantization parameter (QP) affects the following frames as well as the first frame. In this paper, an adaptive peak signal to noise ratio (PSNR)-based initial QP determination algorithm is presented. In the proposed algorithm, a novel linear model is established based on the observation of the relation between the initial QPs and PSNRs of frames. Using the linear model and PSNR results of the encoded GOPs, the proposed algorithm accurately estimates the optimal initial QP which maximizes the PSNR of the current GOP. It is shown by experimental results that the proposed algorithm predicts the optimal initial QP accurately and thus achieves better PSNR performance than that of the existing algorithm.

Adaptive Initial Quantization Parameter Determination for H.264/AVC Video Transcoding

Video adaptation through transcoding can provide both bit-rate reduction and resolution reduction to meet various requirements from display devices to network links. One important issue in video transcoding is the design of rate control algorithm in order to achieve target bit rate by adjusting certain coding parameters. Among them, proper selection of initial quantization parameter (QP) has been shown to induce noticeable impact on the performance of video transcoding scheme. Current approaches in initial QP determination are either too complicated or lacking adequate accuracy. This paper presents an adaptive QP initialization for H.264/AVC transcoding. First, we carefully build the models of R-MSE and QP-PSNR. Then, we introduce an R-QP model and allocate an optimal target buffer to the first frame by considering its temporal importance. The analysis and the R-QP model lead to a novel scheme to determine the initial QP adaptively to achieve more accurate estimation. Experiments have been carried out to demonstrate that substantial gains in objective quality measures can be consistently obtained. Without increasing complexity in transcoding system, the proposed adaptive initial QP scheme outperforms current existing schemes for various video sequences tested in this research.

Efficient one-pass frame level rate control for H.264/AVC

In this paper, an efficient one-pass frame level rate control algorithm is proposed for H.264/AVC, where the two essential problems in rate control, i.e., the budget allocation (BA) and the quantization parameter determination (QPD) are both considered. First, an efficient BA scheme is designed with special consideration of the inter-frame dependency. Accordingly, the error propagation caused by improper QP assignment in the motion compensation process is reduced and the total distortion is kept at a low level. Second, a better QPD method is developed based on an accurate rate model and a second feedback mechanism so that a high rate accuracy is guaranteed. Simulations verified the performance of the proposed algorithm. Compared with the fixed QP coding and the two recommended rate control algorithms (G012-MB and G012-Frame) in H.264/AVC reference software, up to 1.50, 1.12, and 0.94 dB were achieved with a higher rate accuracy in the coding efficiency test defined by ITU-T VCEG. Particularly, a more significant improvement was observed in slow movement scenarios: compared with G012-MB, a gain of 0.80 dB on average and 1.43 dB at maximum was obtained with 66.0% reduction of average rate mismatch. Compared with G012-Frame, the average and maximum gains are 0.34 and 1.06 dB, respectively. While at the same time, the average rate mismatch was reduced by 90.4%. Considering the low computational cost, the proposed algorithm is quite appealing to real-time video applications.

Rate-Distortion Optimization of Rate Control for H.264 With Adaptive Initial Quantization Parameter Determination

A rate-distortion (R-D) optimization rate control (RC) algorithm with adaptive initialization is presented for H.264. First, a linear distortion-quantization (D-Q) model is introduced and thus a close-form solution is developed to derive optimal quantization parameters (Qp)for encoding each macroblock. Then we exploit to determine the initial Qp efficiently and adaptively according to the content of video sequences. The experimental results demonstrate that the proposed algorithm can achieve better R-D performance than that of other two RC algorithms including the algorithm JVT-G012 which is the current recommended RC scheme implemented in the H.264 reference software JM9.5.

Rate Control for H.264 with Two-Step Quantization Parameter Determination but Single-Pass Encoding

We present an efficient rate control strategy for H.264 in order to maximize the video quality by appropriately determining the quantization parameter (QP) for each macroblock. To break the chicken-and-egg dilemma resulting from QP-dependent rate-distortion optimization (RDO) in H.264, a preanalysis phase is conducted to gain the necessary source information, and then the coarse QP is decided for rate-distortion (RD) estimation. After motion estimation, we further refine the QP of each mode using the obtained actual standard deviation of motion-compensated residues. In the encoding process, RDO only performs once for each macroblock, thus one-pass, while QP determination is conducted twice. Therefore, the increase of computational complexity is small compared to that of the JM 9.3 software. Experimental results indicate that our rate control scheme with two-step QP determination but single-pass encoding not only effectively improves the average PSNR but also controls the target bit rates well.