Quantization Parameter Adjustment 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.

Fault-Tolerant Control for Unmanned Marine Vehicles via Quantized Integral Sliding Mode Output Feedback Technique

This paper presents a fault-tolerant control method based on the integral sliding mode (ISM) output feedback technique for the dynamic positioning control of an unmanned marine vehicle (UMV) subject to signal quantization and thruster faults. By using output information and estimates of thruster effectiveness factors, a novel integral sliding manifold is first constructed to maintain that the sliding function of system output equals the one of quantized output, which removes the region restriction that exists in the literature. Then based on the quantized signals of system output, a compensator is designed to introduce some degrees of design flexibility. To conquer the quantization effects, we incorporate a dynamic quantization parameter adjustment strategy and the fault-tolerant technique into the ISM output feedback control algorithm. The relation between the attraction area and quantization range has been revealed for the first time. Finally, the closed-loop stability can be guaranteed from every beginning time in despite of the quantization and thruster faults. Simulation through a typical floating production ship has verified the effectiveness of the proposed method.

Quantized Sliding Mode Fault-Tolerant Control for Unmanned Marine Vehicles with Thruster Saturation

In this paper, the sliding mode technique is used to study the quantized fault-tolerant control of unmanned marine vehicles with thruster saturation. Firstly, the sliding mode surface is constructed according to the full rank decomposition of input matrix, and the stability of sliding mode is guaranteed by linear matrix inequalities. An improved dynamic adjustment scheme of quantization parameter is proposed. Compared with the original adjustment scheme, the relationship between quantization parameter and desired targets is increased, so that the adjustment range of quantization parameters is more comprehensive. The sliding mode controller is combined with quantization parameter adjustment strategy to ensure the asymptotic stability of unmanned marine vehicles system. In addition, compared with the existing research results of quantitative fault tolerance problem without considering saturation, this paper gives a result of the domain of attraction affected by the fault of the thruster. Finally, the superiority of the proposed method is verified by simulation comparison.

Quantized Output-Feedback Control for Unmanned Marine Vehicles With Thruster Faults via Sliding-Mode Technique.

This article is concerned with the quantized output-feedback control problem for unmanned marine vehicles (UMVs) with thruster faults and ocean environment disturbances via a sliding-mode technique. First, based on output information and compensator states, an augmented sliding surface is constructed and sliding-mode stability through linear matrix inequalities can be guaranteed. An improved quantization parameter dynamic adjustment scheme, with a larger quantization parameter adjustment range, is then given to compensate for quantization errors effectively. Combining the quantization parameter adjustment strategy and adaptive mechanism, a novel robust sliding-mode controller is designed to guarantee the asymptotic stability of a closed-loop UMV system. As a result, a smaller lower bound of the thruster fault factor than that of the existing result can be tolerated, which brings more practical applications. Finally, the comparison simulation results have illustrated the effectiveness of the proposed method.

Integral sliding mode fault tolerant control for unmanned surface vessels with quantization: Less iterations

This paper introduces an integral sliding mode quantized control strategy for unmanned surface vessels (USVs) with thruster faults and signal quantization over networks. The main challenge focuses on the co-design of dynamic quantization parameter adjustment strategy (DQPAS) and fault tolerance ability. The existing literature has solved it with a heavy computation burden. To reduce the repeated iteration of quantization parameter, an improved DQPAS with a well-chosen initial value of quantization parameter is designed. Based on it, an integral sliding mode fault tolerant controller with fault estimation is proposed to suppress the oscillation amplitudes of yaw angle and yaw velocity from the very beginning. Finally, comparison simulation results have demonstrated that the derived strategy is effective.

Visual saliency guided perceptual adaptive quantization based on HEVC intra-coding for planetary images.

Due to the limited storage space of spacecraft and downlink bandwidth in the data delivery during planetary exploration, an efficient way for image compression onboard is essential to reduce the volume of acquired data. Applicable for planetary images, this study proposes a perceptual adaptive quantization technique based on Convolutional Neural Network (CNN) and High Efficiency Video Coding (HEVC). This technique is used for bitrate reduction while maintaining the subjective visual quality. The proposed algorithm adaptively determines the Coding Tree Unit (CTU) level Quantization Parameter (QP) values in HEVC intra-coding using the high-level features extracted by CNN. A modified model based on the residual network is exploited to extract the saliency map for a given image automatically. Furthermore, based on the saliency map, a CTU level QP adjustment technique combining global saliency contrast and local saliency perception is exploited to realize a flexible and adaptive bit allocation. Several quantitative performance metrics that efficiently correlate with human perception are used for evaluating image quality. The experimental results reveal that the proposed algorithm achieves better visual quality along with a maximum of 7.17% reduction in the bitrate as compared to the standard HEVC coding.

Fault Tolerant Control for Dynamic Positioning of Unmanned Marine Vehicles Based on T-S Fuzzy Model With Unknown Membership Functions

This paper proposes a novel fault tolerant control strategy for dynamic positioning of unmanned marine vehicles using the quantized feedback sliding mode control technique. Due to the complex ocean environment, the unmanned marine vehicles are modeled as the Takagi-Sugeno fuzzy system with unknown membership functions. When the membership functions are not available, traditional sliding mode control technique becomes infeasible. To tackle this difficulty, a novel quantized sliding mode control strategy based on switching mechanism is designed to compensate for thruster faults effects. In addition, the phenomenon of time-varying delay leads to conservativeness of the existing dynamic quantization parameter adjustment strategy. Then a larger quantization parameter adjustment range, by taking time delay and fault factor into account, is given. Combining the novel sliding mode controller design and the improved dynamic quantization parameter adjustment strategy, the dynamic positioning of unmanned marine vehicles with thruster faults and quantization can be maintained. Finally, the effectiveness of the proposed method is verified through the simulation comparison results.

Sliding mode fault-tolerant control for unmanned marine vehicles with signal quantization and time-delay

This paper deals with the adaptive sliding mode fault-tolerant control problem for unmanned marine vehicles (UMVs) with signal quantization and state time-delay. A unified thruster fault model for UMVs is built by taking bias, partial, total, time-varying stuck, and hard-over faults into account. For UMVs in the network environment, the effects of quantization and state time-delay on UMVs are inevitable. In this situation, adaptive sliding mode technology and dynamic quantization parameter adjustment strategy are combined to compensate for the quantization errors and time-delay effects. Compared with the traditional method, a larger quantization parameter adjustment range is given and a new dynamic quantization parameter adjustment strategy is designed. Further the quantized sliding mode fault-tolerant controller independent of fault detection and diagnosis mechanism is designed for UMVs in the presence of time-delay and various thruster faults to reduce the oscillation amplitudes of the yaw velocity error. The comparison simulations of a typical floating production ship have been provided to demonstrate the effectiveness of the proposed algorithm.

Quantized Sliding Mode Control of Unmanned Marine Vehicles: Various Thruster Faults Tolerated With a Unified Model

This paper investigates quantized sliding mode control of unmanned marine vehicles (UMVs) with thruster faults and nonlinearities. We give a unified model to accommodate different types of thruster faults (e.g., partial, total, time-varying stuck, hard-over, and bias faults) in a common framework, which is significant because existing methods can only address them separately in a fault-specific manner. To eliminate the quantization effect induced by the communication channel by which the UMV outputs (e.g., position and velocity) and the control inputs are transmitted to and from the remote control station, a new dynamic uniform quantizer with an adjustable range of sensitivity is given. Via flexible choice of parameters, the adjustment range can fall within that of the existing results in the fault-free case. A quantized sliding mode controller and a dynamic quantization parameter adjustment strategy are then developed to suppress oscillation amplitudes of the yaw velocity error and the yaw angle in the presence of thruster faults. Simulation studies have verified the effectiveness of the proposed method.

A perception based bit allocation for 3DTV broadcasting

Perceptually adaptive bit allocation plays vital roles in efficient rate control to achieve rate distortion optimization in terms of perceptual video coding. This paper proposes a perceptually improved bit allocation scheme by employing a more accurate distortion model inspired by a state-of-the-art perceptual video quality metric. The contributions of this paper mainly involve the following three aspects. Firstly, a perceptual rate-distortion model is developed to shape the framework of perceptual video coding. Secondly, based on the characteristics of the model, an adaptively frame-level bit allocation scheme is proposed using the rate distortion optimization technology. Meanwhile, the status of the encoder buffer is also taken into account to avoid overflow or underflow. Finally, a macroblock-level quantization parameter adjustment is presented to improve perceptual video quality. Experimental results demonstrate that the whole proposed bit allocation scheme achieves better perceptual rate-distortion performance and guarantees the accuracy of rate control well.

Integral Sliding Mode Fault-Tolerant Control for Uncertain Linear Systems Over Networks With Signals Quantization.

In this paper, a new robust fault-tolerant compensation control method for uncertain linear systems over networks is proposed, where only quantized signals are assumed to be available. This approach is based on the integral sliding mode (ISM) method where two kinds of integral sliding surfaces are constructed. One is the continuous-state-dependent surface with the aim of sliding mode stability analysis and the other is the quantization-state-dependent surface, which is used for ISM controller design. A scheme that combines the adaptive ISM controller and quantization parameter adjustment strategy is then proposed. Through utilizing H∞ control analytical technique, once the system is in the sliding mode, the nature of performing disturbance attenuation and fault tolerance from the initial time can be found without requiring any fault information. Finally, the effectiveness of our proposed ISM control fault-tolerant schemes against quantization errors is demonstrated in the simulation.

Region-of-Interest Based Conversational HEVC Coding with Hierarchical Perception Model of Face

In this paper, we propose a region-of-interest (ROI) based HEVC coding approach for conversational videos, with a novel hierarchical perception model of face (HP model), to improve the perceived visual quality of state-of-the-art HEVC standard. In contrast to the previous ROI-based video coding approaches, this novel HP model allows the unequal importance of facial features (e.g., the eyes and mouth) within the facial region, by generating a pixel-wise weight map. Benefitting from such a perception model, the adaptive coding tree unit (CTU) partition structure is developed to alleviate the encoding complexity of HEVC, without any degradation of the visual quality in facial regions, especially in the regions of facial features. Subsequently, for the rate control in HEVC a weight-based unified rate-quantization (URQ) scheme, instead of the conventional pixel-based URQ scheme, is proposed to adaptively adjust the value of quantization parameter (QP). Such an adaptive adjustment of QPs is capable of allocating more bits to the face/facial features with respect to our HP model, and as a result, the visual quality of face, in particular facial features, can be enhanced for conversational HEVC coding. Finally, the experimental results show that the perceived visual quality of our approach is greatly improved, with even less encoding time, for conversational video coding on the HEVC platform.

FMO-based H.264 frame layer rate control for low bit rate video transmission

Abstract The use of flexible macroblock ordering (FMO) in H.264/AVC improves error resiliency at the expense of reduced coding efficiency with added overhead bits for slice headers and signalling. The trade-off is most severe at low bit rates, where header bits occupy a significant portion of the total bit budget. To better manage the rate and improve coding efficiency, we propose enhancements to the H.264/AVC frame layer rate control, which take into consideration the effects of using FMO for video transmission. In this article, we propose a new header bits model, an enhanced frame complexity measure, a bit allocation and a quantization parameter adjustment scheme. Simulation results show that the proposed improvements achieve better visual quality compared with the JM 9.2 frame layer rate control with FMO enabled using a different number of slice groups. Using FMO as an error resilient tool with better rate management is suitable in applications that have limited bandwidth and in error prone environments such as video transmission for mobile terminals.

Design of a mobile video streaming system using adaptive spatial resolution control

An efficient mobile video streaming system needs to cope with unstable network bandwidth and limited battery life. We propose a novel streaming system which jointly considers picture quality, bit-rate and energy consumption. Reducing the spatial resolution of a video stream adaptively proves to be more efficient in terms of picture quality and energy consumption than conventional rate control using only adjustment of quantization parameter. We apply the same scheme to scalable coding for large-scale mobile video streaming. This extends the adaptation of an SVC stream to lower bit-rates, while maintaining temporal stability. Our approach has been shown to improve picture quality by approximately 0.5 dB in low bit-rate conditions, and also reduces energy consumption by more than 50% compared to conventional video streaming.

On Lagrange multiplier and quantizer adjustment for H.264 frame-layer video rate control

H.264/AVC encoder employs a complex mode-decision technique based on rate-distortion optimization. It calculates rate-distortion cost (RDcost) for all possible modes to choose the best one having the minimum RDcost. This paper presents a frame-layer rate control for H.264/AVC that computes the Lagrange multiplier (/spl lambda//sub MODE/) for mode decision by using a quantization parameter (QP) which may be different from that used for encoding. At the same time, we also compare actual bits produced by previous macroblocks (MBs) with the total bits allocated to these MBs to further modify /spl lambda//sub MODE/. The objective of these measures aims to produce bits as close to the frame target bits for rate control as possible. This is very important in the case of low-bit-rate tight buffer applications. In order to obtain an accurate QP for a frame, we employ a complexity-based bit-allocation scheme and a QP adjustment method. Simulation results comparing with the H.264 Joint Video Team (JVT) rate control method show that the H.264 encoder, using the proposed algorithm, achieves a visual quality improvement of about 0.56 dB, performs better for buffer overflow and underflow, and achieves a smaller PSNR deviation.