Initial Quantization Parameter Research Articles

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.

Data-Driven Rate Control for Rate-Distortion Optimization in HEVC Based on Simplified Effective Initial QP Learning

Different from the conventional calculative methods, a learning-based initial quantization parameter (LIQP) method is proposed in this paper to improve rate control of high efficiency video coding (H.265). First, the framework for initial quantization parameter (QP) learning is proposed, where a novel equivalent approach to build the benchmark labels is proposed using the single rate-distortion (R-D) pair in each initial QP testing. With the criterion of maximizing the prediction accuracy of initial QPs, features and parameters of the learning model are refined. Instead of the traditionally used target bits per pixel (bpp) for intraframe, the target bpp for all remaining frames is proposed to avoid the empirical setting on intracoding bits, and thus the related inaccuracy can be prevented. We clearly present the motivations of the proposed LIQP method, as well as the reasons for the extracted features and model parameters. The proposed LIQP method outperforms the latest HM-16.14 by achieving significant gains on R-D performance (−15.48% BD-BR and 0.782 dB BD-PSNR gains), quality smoothness (1.581 dB versus 2.598 dB), and more stable buffer occupancy control, with similar high bit rate accuracy (99.84% versus 99.87%), and can also work well for scene change cases.

Determination of Optimum Quantization Parameters in Residual Quad-Tree of HEVC Based on Perceptual Quality

This article proposes a video encoding method at the residual quad-tree (RQT) level of high-efficiency video coding (HEVC) for JND model-based perceptual coding. This method performs perceptual encoding considering the luminance adaptation characteristics of the human visual system at the RQT level, which determines the partitioning information of the transform unit after determining the motion vectors through motion estimation (a highly complex module in an encoder). In each RQT stage, the proposed algorithm determines the maximum quantization parameter (QP) that reduces the bitrate and simultaneously maintains similar subjective quality, i.e., ensuring no visual quality degradation based on the JND model compared to the initial QP value. To evaluate the performance of the proposed method, a JND model-based RQT-level multi-loop encoding method is applied to the HM16.0 HEVC reference software. Experimental results with a random access configuration of the common test condition show that the bitrate is reduced, on average, by 5.78% and 10% for Class A and Class B videos, respectively; the maximum reduction is 25.3% with the almost same visual quality.

Adaptive Gradient Information and BFGS Based Inter Frame Rate Control for High Efficiency Video Coding

In order to meet the emerging demands of high-fidelity video services, a new video coding standard — High Efficiency Video Coding (HEVC) is developed to improve the compression performance of high definition (HD) videos and save half of the bitrate for the same perceptual video quality compared with H.264/Advanced Video Coding (AVC). Rate control still plays a significant role in HD video data transmission via the communication channel. However, R-lambda model based HEVC rate control algorithm does not take the relationship between the encoding complexity and Human Visual System (HVS) into account, what’s more, the convergence speed of Least Mean Square (LMS) algorithm is slow. In this paper, an adaptive gradient information and Broyden Fletcher Goldfarb Shanno (BFGS) based R-lambda model (GBRL) is proposed for the inter frame rate control, where the gradient based on Sobel operator can effectively measure the frame-content complexity and BFGS algorithm converges speedily than LMS algorithm. Experimental results show that the proposed GBRL method can achieve bitrate error reduction and peak signal to noise ratio (PSNR) improvement especially for the sequences with large motion, compared to the state-of-the-art rate control methods. In addition, if the optimal initial quantization parameter (QP) prediction model based on linear regression can be incorporated into the proposed GBRL method, the performance of rate control can be further improved.

Inter-View Dependency-Based Rate Control for 3D-HEVC

We propose an inter-view dependency-based rate control (RC) algorithm for 3D extension of high efficiency video coding (HEVC). First, considering the rate-distortion (R-D) dependency between the synthesized views and the input views (including texture videos and depth maps), a synthesized view distortion model is derived. Second, a novel distortion model for dependent views is proposed by investigating the inter-view dependency between the base and dependent views. Based on these two distortion models, a joint optimal bit allocation strategy (including texture/depth level, view level, and frame level) is developed to allocate target bits for both texture videos and depth maps of different views. Furthermore, an effective initial quantization parameter decision scheme considering the characteristics of the input video content is presented. Extensive experimental results exhibit that the proposed scheme achieves a higher rate control accuracy and provides a better R-D performance than the state-of-the-art RC algorithms.

Pyramid coding based rate control for constant bit rate video streaming

In this paper, a novel pyramid coding based rate control scheme is proposed for video streaming applications constrained by a constant channel bandwidth. To achieve the target bit rate with the best quality, the initial quantization parameter (QP) is determined by the average spatio-temporal complexity of the sequence, its resolution and the target bit rate. Simple linear estimation models are then used to predict the number of bits that would be necessary to encode a frame for a given complexity and QP. The experimental results demonstrate that the proposed rate control scheme significantly outperforms the existing rate control scheme in the Joint Model (JM) reference software in terms of Peak Signal to Noise Ratio (PSNR) and consistent perceptual visual quality while achieving the target bit rate. Finally, the proposed scheme is validated through experimental evaluation over a miniature test-bed.

JND 모델을 사용한 코딩 유닛 레벨 멀티-루프 인코딩 기반의 비디오 압축 방법

본 논문에서는 주변의 밝기에 대한 HVS의 민감도를 모델링한 JND (Just Noticeable Difference)를 비디오 코딩에 적용함으로써, JND 모델에 따른 임계치를 기준으로 현재 코딩 유닛에 적용 가능한 최대 양자화 파라미터를 결정하여 유사한 주관적 화질에서 비트율을 절감시키는 방법을 제안한다. 제안하는 방법은 입력된 현재 코딩 유닛에 대하여 기준이 되는 양자화 파라미터가 적용된 복원 신호 대비 더 높은 양자화 파라미터를 적용한 복원 신호가 JND 관점에서 유사하게 인지되는 경우에 더 높은 양자화 파라미터를 선택함으로써 비트율을 절감시킨다. 제안하는 알고리즘의 성능 검증을 위하여 최신 비디오 압축 표준인 HEVC (High Efficiency Video Coding)의 참조 소프트웨어인 HM16.0에 본 알고리즘을 적용하였으며, HM16.0을 통해 압축된 영상 대비 유사한 화질에서 최대 20.21%, 평균적으로 약 6.18%의 비트율 절감을 달성하였다.

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.

A Simple and High Performing Rate Control Initialization Method for H.264 AVC Coding Based on Motion Vector Map and Spatial Complexity at Low Bitrate

The temporal complexity of video sequences can be characterized by motion vector map which consists of motion vectors of each macroblock (MB). In order to obtain the optimal initial QP (quantization parameter) for the various video sequences which have different spatial and temporal complexities, this paper proposes a simple and high performance initial QP determining method based on motion vector map and temporal complexity to decide an initial QP in given target bit rate. The proposed algorithm produces the reconstructed video sequences with outstanding and stable quality. For any video sequences, the initial QP can be easily determined from matrices by target bit rate and mapped spatial complexity using proposed mapping method. Experimental results show that the proposed algorithm can show more outstanding objective and subjective performance than other conventional determining methods.

A novel macroblock level rate control method for stereo video coding.

To compress stereo video effectively, this paper proposes a novel macroblock (MB) level rate control method based on binocular perception. A binocular just-notification difference (BJND) model based on the parallax matching is first used to describe binocular perception. Then, the proposed rate control method is performed in stereo video coding with four levels, namely, view level, group-of-pictures (GOP) level, frame level, and MB level. In the view level, different proportions of bitrates are allocated for the left and right views of stereo video according to the prestatistical rate allocation proportion. In the GOP level, the total number of bitrates allocated to each GOP is computed and the initial quantization parameter of each GOP is set. In the frame level, the target bits allocated to each frame are computed. In the MB level, visual perception factor, which is measured by the BJND value of MB, is used to adjust the MB level bit allocation, so that the rate control results in line with the human visual characteristics. Experimental results show that the proposed method can control the bitrate more accurately and get better subjective quality of stereo video, compared with other methods.

Spatial Characteristic Based Rate Control Initialization Method for Conversational Video Communication of H.264/AVC Using Linear Prediction

In this paper, we propose a method of initializing the quantization parameter ( QP ) in H.264 rate control algorithm based on spatial characteristic of conversational video. Primarily, we choose the fourteen various conversational videos and calculate the complexity of the macroblock ( MB ) using variance of MB . The spatial characteristic of each video can be quantized by the proportion of the number of complex MB in the first frame. And then we find their optimal initial QP s which can guarantee that video sequences have consistent quality by minimizing the variation of QP s in a GOP , while ensuring the minimizing actual encoding bit rate closer to the target bit rate over various low bit rates. And then we propose the fitted models of optimal initial QP s against spatial characteristic over different low bit rates. The proposed model can be used to determine optimal initial QP to guarantee consistent quality and to meet target bit rate simultaneously. The objective and subjective simulation results show that the proposed method achieves better balance quality than JM10.2 and previous research result

An Enhanced Rate Control Initialization Method for H.264 based on Image Quality Balance of GOP Using Support Vector Machines

In this paper, we propose an enhanced method of initializing the quantization parameter ( QP ) in H.264 rate control algorithm based on image quality balance of GOP (Group of Pictures) using support vector machines ( SVM s). Primarily, we analyze characteristics of some typical video sequences by motion vectors. And then we choose four video sequences with different characteristics and computer their spatial and temporal complexities and the optimal initial QP s which can guarantee to generate video sequences with consistent quality by minimizing the variation of QP s in a GOP , while ensuring the actual encoding bit rate closer to the target bit rate in various bit rates by proposed selection method of optimal initial QP . We utilize SVM s that can detect the optimal parameters by genetic algorithm to train the regression function of the extracted features that are the spatial and temporal complexities as well as given the target bit rates of sample video sequences and target that is optimal initial QP s. When any video sequence is given under any target bit rate, its spatial complexity is calculated and mapped to one of four samples through the proposed mapping method. Finally, its optimal initial QP is determined by regression function according to the mapped spatial complexity, corresponding temporal complexity of sample video sequence and given target bit rate

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.

An efficient intra-frame rate control algorithm for H.264/AVC video coding

Intra-frame plays a significant role in improving video quality for rate control of H.264/AVC. In this paper, an efficient intra-frame rate control algorithm is proposed for H.264/AVC video coding. The proposed scheme adjusts the quantization parameter (QP) of intra-frame adaptively according to intra-frame buffer fullness ratio, current buffer fullness ratio, and skipped frame ratio. Experimental results demonstrate that for a set of typical testing sequences, the proposed scheme can obtain accurate target bit rate, better peak signal-to-noise ratio (PSNR) performance and reduce the number of skipped frames significantly, when compared with existing schemes. More importantly, the proposed scheme is very flexible for different initial QPs and target bits.

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Rate control is a critical issue in H.264/AVC video coding standard because it suffers from some shortcomings that make the bit allocation process not optimal. This leads to a video quality that may vary significantly from frame to frame. Our aim is to enhance the rate control efficiency in H.264/AVC baseline profile by handling two of its defects: the initial quantization parameter (QP) estimation for Intra-Frames (I-Frames) and the target number of bits determination for Inter-Frames (P-Frames) encoding. First, we propose a Rate-Quantization (R-Q) model for the I-Frame constructed empirically after extensive experiments. The optimal initial QP calculation is based on both target bit-rate and I-Frame complexity. The I-Frame target bit-rate is derived from the global target bit-rate by using a new non-linear model. Secondly, we propose an enhancement of the bit allocation process by exploiting frame complexity measures. The target number of bits determination for P-Frames is adjusted by combining two temporal measures: the first is a motion ratio based on actual bits used to encode previous frames; the second measure exploits the difference between two consecutive frames and the histogram of this difference. The simulation results, carried out using the JM15.0 reference software and the JVT-O016 rate control algorithm, show that the right choice of initial QP for I-Frame and first P-Frame allows improvement of both the bit-rate and peak signal-to-noise ratio (PSNR). Finally, the Inter-Frame bit allocation process further improves the bit-rates while keeping the same PSNR improvement (up to +1.33 dB/+2 dB for QCIF/CIF resolutions). Moreover, this process reduces the buffer level variation leading to a more consistent quality of reconstructed videos.

Novel Rate-Quantization Model-Based Rate Control With Adaptive Initialization for Spatial Scalable Video Coding

A novel spatial-layer rate-control algorithm is proposed for scalable video coding (SVC). First, by analyzing the relationship among the best initial quantization parameter ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ), channel bandwidth, and the initial frames' complexity measure, an adaptive <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> -initialization model is introduced to determine the starting <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> value for not only the base layer but also the spatial enhancement layers of SVC. Then, a two-stage <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> -determination scheme is designed to improve the rate-control performance for the spatial-layer SVC with an efficient frame-complexity prediction method and an adaptive model-parameter update technique employed. Experimental results demonstrate the effectiveness of the proposed <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> -initialization scheme and the two-stage <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> -determination algorithm. By comparison with two other benchmark rate-control algorithms, the proposed rate-control algorithm is able to control constrained bit rates accurately with better rate-distortion performance.

A New Rate Control Algorithm based on Statistical Analysis for MVC

Rate control is one of important tools in multi-view video coding (MVC). This paper presents a new rate control algorithm for MVC by analyzing the rate allocation proportion among different types of views. The proposed algorithm is performed on three levels, that is, view level, group-of-pictures (GOP) level and frame level. Firstly, we reasonably allocate bit-rate among views based on the statistical analysis in the view level. Then, in the GOP level, the initial quantization parameter (QP) of each GOP is set according to the QP values of B frames. Finally, the frame complexity is used to regulate the target bit for each frame. Experimental results show that the proposed algorithm can accurately control bit-rate to satisfy the requirements of multi-view video systems.

A rate-control algorithm using inter-layer information for H.264/SVC for low-delay applications

This paper proposes a novel frame-level rate-control scheme for H.264/SVC for low-delay applications. The trend of the Mean Absolute Difference (MAD) (after motion compensation) of the reference layer is used as the inter-layer information for Inter-layer MAD prediction, which is combined with Intra-layer MAD prediction to predict the MAD of the enhancement layers (EL) more accurately. By considering the influence from both the texture and nontexture information, the varying picture complexity and feedback information from the actual encoding results are combined to achieve an accurate bit-allocation. A coarse-to-fine initial quantization parameter (QP) selection method is proposed to refine the initial QP of the EL according to the channel condition and the video sequence characteristics. Experimental results demonstrate that the proposed scheme can obtain high and smooth PSNR, and the output bit-rate is close to the target bit-rate. Also, the proposed scheme can avoid serious buffer fullness fluctuation and reduce skipped frames in the video coding.

Adaptive video coding control for real-time H.264/AVC encoder

In this paper, we present a new adaptive video coding control for real-time H.264/AVC encoding system. The main techniques include: (1) the initial quantization parameter (QP) decision scheme is based on Laplacian of Gaussian (LoG) operators; (2) the MB-level QP calculation is based on the spatio-temporal correlation, in which the computation is less than the quadratic model used by H.264/AVC; (3) the adaptive GOP structure is proposed, in which the I-frame is adaptively replaced by an enhancement P-frame to improve the coding efficiency; (4) the scene change is detected with the complexity of adjacent inter-frames and the appropriate QP is re-calculated for the scene-change frame. The proposed algorithm is not only to save the computational complexity but also to improve coding quality. Compared to the JM12.4 reference under various sequences testing, the proposed algorithm can decrease coding time by 64.5% and improve PSNR by 1.52 dB while keeping the same bit-rate.