Adaptive Quantization Parameter Research Articles

Adaptive QP algorithm for depth range prediction and encoding output in virtual reality video encoding process.

In order to reduce the encoding complexity and stream size, improve the encoding performance and further improve the compression performance, the depth prediction partition encoding is studied in this paper. In terms of pattern selection strategy, optimization analysis is carried out based on fast strategic decision-making methods to ensure the comprehensiveness of data processing. In the design of adaptive strategies, different adaptive quantization parameter adjustment strategies are adopted for the equatorial and polar regions by considering the different levels of user attention in 360 degree virtual reality videos. The purpose is to achieve the optimal balance between distortion and stream size, thereby managing the output stream size while maintaining video quality. The results showed that this strategy achieved a maximum reduction of 2.92% in bit rate and an average reduction of 1.76%. The average coding time could be saved by 39.28%, and the average reconstruction quality was 0.043, with almost no quality loss detected by the audience. At the same time, the model demonstrated excellent performance in sequences of 4K, 6K, and 8K. The proposed deep partitioning adaptive strategy has significant improvements in video encoding quality and efficiency, which can improve encoding efficiency while ensuring video quality.

Cracks-suppression perceptual geometry coding for dynamic point clouds

Dynamic point clouds can effectively describe 3D objects and natural scenes, providing users with an immersive visual experience, but their huge amount of data requires efficient compression tools. To this end, the video-based point cloud compression (V-PCC) standard was developed, however, it may lead to cracks in the compressed point cloud at low bitrates. To solve the problem, this paper proposes a cracks-suppression perceptual geometry coding method for dynamic point cloud. Firstly, considering that the edge regions of 2D geometry patches in V-PCC are prone to cracks, a prior knowledge based crack region detection and preprocessing scheme is designed to reduce cracks. Secondly, considering the unique perceptual geometry characteristics of point cloud, a projected geometry curvature based structural similarity (PGC-SSIM) is proposed to evaluate geometry quality of point clouds, which contains the geometric perception information of point cloud, and is more consistent with the human visual perception. Finally, based on the PGC-SSIM, an adaptive quantization parameter adjustment strategy is designed for rate-distortion optimization in geometry coding of dynamic point clouds. The experimental results show that the proposed method can effectively reduce cracks in the compressed point cloud without reducing the coding performance compared to the V-PCC anchor. Moreover, the presented PGC-SSIM can be used to improve the visual quality of the compressed point cloud.

Coding–Decoding-Based Sliding Mode Control for Markovian Jump Systems Under Constrained Bit Rate: An Adaptive Quantizer Approach

This paper investigates the asynchronous sliding mode control (SMC) issue for uncertain hidden Markovian jump systems (MJSs) under constrained bit rate. An improved coding-decoding procedure with state-dependent adaptive quantization parameters is established to enable the controller to decode state and mode information from the system and the detector, respectively. Based on this procedure, a decoded-data-based asynchronous SMC strategy is provided and sufficient conditions are developed to ensure that the closed-loop dynamics are exponentially ultimately bounded and the system state is driven onto a sliding region simultaneously in the sense of mean square. The desired parameters of the quantizer and controller are obtained by solving an optimization problem, in which the objective function is constructed by using the trade-off between the ultimate state bound and the decay rate. Moreover, the integrative design of bit rate allocation protocol and quantizer as well as control parameters are converted into a nonlinear programming problem with integer constraint, which is solved by means of an improved sparrow search algorithm. Finally, a direct current motor system is employed to illustrate the effectiveness of the present approach under three different cases.

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.

Rate distortion optimization with adaptive content modeling for random-access versatile video coding

In this paper, we study the capability of improving the rate-distortion (RD) performance based on the adaptive content modeling in the Versatile Video Coding (VVC) standard. In particular, the frame-level dependent relationships and inherent RD relationship are explored. As such, the rate dependency, distortion dependency and inherent RD characteristics are fully utilized in the global rate distortion optimization (RDO) process, and the quantization parameter (QP) for each frame could be adaptively solved. To facilitate the adaptive QP calculation, a two-pass coding strategy is proposed. In the first-pass coding, the video statistics are sufficiently collected with the proposed Dual Motion Compensation and Residual Coding (DMCRC) method to generate the parameters for the content-aware models. During the second-pass coding, the optimal QP at the frame level is obtained by optimizing the global RD performance with the dependent and inherent models. The proposed algorithm is implemented on VVC test model (VTM-4.0) and achieves significant performance gain for test sequences with constant and varying scenes.

High-Efficiency Video Coder in Pruned Environment Using Adaptive Quantization Parameter Selection

The high-efficiency video coder (HEVC) is one of the most advanced techniques used in growing real-time multimedia applications today. However, they require large bandwidth for transmission through bandwidth, and bandwidth varies with different video sequences/formats. This paper proposes an adaptive information-based variable quantization matrix (AI-VQM) developed for different video formats having variable energy levels. The quantization method is adapted based on video sequence using statistical analysis, improving bit budget, quality and complexity reduction. Further, to have precise control over bit rate and quality, a multi-constraint prune algorithm is proposed in the second stage of the AI-VQM technique for pre-calculating K numbers of paths. The same should be handy to self-adapt and choose one of the K-path automatically in dynamically changing bandwidth availability as per requirement after extensive testing of the proposed algorithm in the multi-constraint environment for multiple paths and evaluating the performance based on peak signal to noise ratio (PSNR), bit-budget and time complexity for different videos a noticeable improvement in rate-distortion (RD) performance is achieved. Using the proposed AI-VQM technique, more feasible and efficient video sequences are achieved with less loss in PSNR than the variable quantization method (VQM) algorithm with approximately a rise of 10%–20% based on different video sequences/formats

Video coding optimization in AVS2

Chinese second generation of the Audio Video Coding Standard, known as the AVS2, competing with HEVC/H.265 and AV1, has become a well-known video compression standard. Many unique tools have been developed and incorporated in AVS2. This paper proposes several encoder optimization schemes with respect to rate-distortion optimization (RDO). Specifically, by exploiting the close relationship between the total number of referenced pictures and the hierarchy of reference structure, a reference structure determined parameter (RSDP) algorithm reallocates Lagrange multiplier. Moreover, an adaptive quantization parameter offset (AQPO) algorithm is provided at both picture-level and Groups of Pictures (GoP)-level to adjust quantization parameters adaptively on top of the preassigned ones. Both RSDP algorithm and AQPO algorithm have already been adopted by AVS2 and incorporated in its reference software. Experimental results show that in the low-delay, RSDP and AQPO achieved savings of 1.35% and 1.26% on BDBR, respectively.

Adaptive QP offset selection algorithm for virtual reality 360-degree video based on CTU complexity

Virtual reality 360-degree video requires ultra-high resolution to provide realistic feeling and dynamic perspective. Huge data volume brings new challenges to coding and transmission. Quantization parameter (QP) is one of the key parameters to control output bitrate and reconstruction quality during coding process. Many QP offset selection algorithms designed for this kind of video are based on latitude or Equirectangular Projection (ERP) weight maps, which cannot adapt to the situation of the flat block in tropical area or the complex block in polar area. In this paper, a new metric to measure complexity of Coding Tree Unit (CTU) is designed, and an adaptive QP offset selection algorithm is proposed based on CTU complexity to improve the quantization process. Each CTU is classified into one of the five categories according to its complexity, and then different QP offset value is determined for each category. By improving the quality of the visually sensitive area and reducing the bitrate of the flat one, the efficiency of the encoder is improved. The experimental results show that, compared with the HM16.20, the WS-PSNR increases by 0.40 dB, the BD-rate reduces by 1.99%, and the quality of visually sensitive areas has improved significantly.

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.

An Adaptive QP Adjustment of Multimedia over Heterogeneous Wireless Networks

When videos are transmitted to the moving vehicle through heterogeneous networks, the mobility will frequently trigger the vertical handoff of networks. This may cause large fluctuation of channel bandwidth and will affect the Quality of Experience(QoE) of videos. In order to effectively solve the problem, an adaptive video transmission mechanism was proposed to guarantee the video quality. An information feedback link from the vehicle terminal was designed first. After analyzing the queue length of the vehicle receiver buffer and its future variation trend, the terminal fed back the judgment and prediction and the video’s encoding Quantization Parameters(QP) were updated at the sender. Simulation results show that the variation of video encoding rates in our algorithm could properly adapt to the bandwidth fluctuation of heterogeneous networks. This mechanism not only makes full use of the wireless bandwidth resource, but also effectively avoids video interruption and ensures the video QoE.

Adaptive Quantization Parameter Selection For H.265/HEVC by Employing Inter-Frame Dependency

Rate-distortion optimization (RDO) is widely applied in video coding, which aims at minimizing the coding distortion at a target bitrate. Conventionally, RDO is performed independently on each individual frame to avoid high computational complexity. However, extensive use of temporal/spatial predictions result in strong coding dependencies among neighboring frames, which make the current RDO be non-optimally used. To further improve video coding performance, it would be desirable to perform global RDO among a group of neighboring frames while maintaining approximately the same coding complexity. In this paper, the problem of global RDO is studied by jointly determining the quantization parameters (QPs) for a group of neighboring frames. Specifically, an adaptive frame-level QP selection algorithm is proposed for the H.265/HEVC random access coding by taking into account the inter-frame dependency. To measure the inter-frame dependency, a model based on the energy of prediction residuals is first established. With the help of the model, the problem of global RDO is then analyzed for the hierarchical coding structure in H.265/HEVC. Finally, the QP and the corresponding Lagrangian multiplier for each coding frame are determined adaptively by considering the total impact of its coding distortion on that of future frames in the encoding order. Experimental results show that in comparison with HM-16.0, the proposed algorithm reduces, on average, the BD-rate by 3.49% with negligible increase of encoding time. In addition, the quality fluctuation of the coded video by the proposed algorithm is lower than that by HM-16.0.

Imperceptible watermarking for security of fundus images in tele-ophthalmology applications and computer-aided diagnosis of retina diseases

Background and objectivesThe authentication and integrity verification of medical images is a critical and growing issue for patients in e-health services. Accurate identification of medical images and patient verification is an essential requirement to prevent error in medical diagnosis. The proposed work presents an imperceptible watermarking system to address the security issue of medical fundus images for tele-ophthalmology applications and computer aided automated diagnosis of retinal diseases. MethodsIn the proposed work, patient identity is embedded in fundus image in singular value decomposition domain with adaptive quantization parameter to maintain perceptual transparency for variety of fundus images like healthy fundus or disease affected image. In the proposed method insertion of watermark in fundus image does not affect the automatic image processing diagnosis of retinal objects & pathologies which ensure uncompromised computer-based diagnosis associated with fundus image. Patient ID is correctly recovered from watermarked fundus image for integrity verification of fundus image at the diagnosis centre. ResultsThe proposed watermarking system is tested in a comprehensive database of fundus images and results are convincing. Experimentalresults indicate that proposed watermarking method is imperceptible and it does not affect computer vision based automated diagnosis of retinal diseases. ConclusionsCorrect recovery of patient ID from watermarked fundus image makes the proposed watermarking system applicable for authentication of fundus images for computer aided diagnosis and Tele-ophthalmology applications.

P.7.f.002 - Prospective, observational cohort study of JAKE™, an autism knowledge

The authentication and integrity verification of medical images is a critical and growing issue for patients in e-health services. Accurate identification of medical images and patient verification is an essential requirement to prevent error in medical diagnosis. The proposed work presents an imperceptible watermarking system to address the security issue of medical fundus images for tele-ophthalmology applications and computer aided automated diagnosis of retinal diseases.In the proposed work, patient identity is embedded in fundus image in singular value decomposition domain with adaptive quantization parameter to maintain perceptual transparency for variety of fundus images like healthy fundus or disease affected image. In the proposed method insertion of watermark in fundus image does not affect the automatic image processing diagnosis of retinal objects & pathologies which ensure uncompromised computer-based diagnosis associated with fundus image. Patient ID is correctly recovered from watermarked fundus image for integrity verification of fundus image at the diagnosis centre.The proposed watermarking system is tested in a comprehensive database of fundus images and results are convincing.results indicate that proposed watermarking method is imperceptible and it does not affect computer vision based automated diagnosis of retinal diseases.Correct recovery of patient ID from watermarked fundus image makes the proposed watermarking system applicable for authentication of fundus images for computer aided diagnosis and Tele-ophthalmology applications.

An Improved Inter-Frame Prediction Algorithm for Video Coding Based on Fractal and H.264

Video compression has become more and more important nowadays along with the increasing application of video sequences and rapidly growing resolution of them. H.264 is a widely applied video coding standard for academic and commercial purposes. And fractal theory is one of the most active branches in modern mathematics, which has shown a great potential in compression. In this paper, this study proposes an improved inter prediction algorithm for video coding based on fractal theory and H.264. This study take the same approach to make intra predictions as H.264 and this study adopt the fractal theory to make inter predictions. Some improvements are introduced in this algorithm. First, luminance and chrominance components are coded separately and the partitions are no longer associated as in H.264. Second, the partition mode for chrominance components has been changed and the block size now rages from $16\times 16$ to $4\times 4$ , which is the same as luminance components. Third, this study introduced adaptive quantization parameter offset, changing the offset for every frame in the quantization process to acquire better reconstructed image. Comparison between the improved algorithm, the original fractal compress algorithm and JM19.0 (The latest H.264/AVC reference software) confirms a slightly increase in Peak Signal-to-Noise Ratio, a significant decrease in bitrate while the time consumed for compression remains less than 60% of that using JM19.0.

저지연 HEVC 부호화기를 위한 효율적인 프레임별 양자화 파라미터 할당 방법

본 논문에서는 HEVC 부호화기에서의 주어진 Group of picture(GOP) 구조에 맞추어 양자화 파라미터(Quantization parameter, QP)를 효율적으로 할당하는 방법을 제안한다. HEVC에서는 주어진 GOP 설정에 따라 각 비디오 프레임에 다른 QP값들을 할당할 수 있다. 특히, 낮은 QP값은 중요한 프레임에 할당시키고, 높은 QP값은 덜 중요한 프레임들에 할당하는 QP 변화 전략을 통해 압축률 증가를 꾀할 수 있다. 그러나 지금까지 효율적으로 QP를 할당하는 방법에 대한 정밀한 분석은 철저히 이루어진 바가 없다. HEVC 참조소프트웨어 부호화기에서도 단지 단조로운 QP 할당 방식만을 사용하고 있을 뿐이다. 본 제안기술은 QP할당을 각 GOP마다 적응적으로 하는 방식으로써, 그 기반은 GOP간의 시간적인 동적 활동 특성들을 활용한다는 것에 있다. 실험 결과, 저지연 부호화 환경설정에서 제안기술은 HEVC 테스트 모델(HM)과 비교하여 BD-rate의 관점으로 7.3%의 압축률을 더 이루었으며, 타 QP 할당방식 연구보다도 평균적으로 압축성능이 우월함을 확인하였다. In this paper, we propose an efficient assignment method that assigns quantization parameter (QP) in accordance with group of picture (GOP) structure given in HEVC encoder. Each video frames can have difference QP values based on given GOP configuration for HEVC encoding. Particularly, for important frames we can assign low QP values, and vice versa. However, there has not been thorough investigation on efficient QP assignment method by far. Even in HEVC reference software encoder, only monotonic QP assignment method is employed. Thus, the proposed method assign adaptive QP values to each GOP so that temporal dynamic activity between GOPs can be exploited. Through the experiment, the proposed method showed a 7.3% gain of compression performance in terms of BD-rate compared to HEVC test model (HM) in low-delay configuration, and outperformed the existing QP assignment study on average.

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.

Adaptive Quantization-Parameter Clip Scheme for Smooth Quality in H.264/AVC

In this paper, we investigate the issues over the smooth quality and the smooth bit rate during rate control (RC) in H.264/AVC. An adaptive quantization-parameter (Q(p)) clip scheme is proposed to optimize the quality smoothness while keeping the bit-rate fluctuation at an acceptable level. First, the frame complexity variation is studied by defining a complexity ratio between two nearby frames. Second, the range of the generated bits is analyzed to prevent the encoder buffer from overflow and underflow. Third, based on the safe range of the generated bits, an optimal Q(p) clip range is developed to reduce the quality fluctuation. Experimental results demonstrate that the proposed Q(p) clip scheme can achieve excellent performance in quality smoothness and buffer regulation.