Rate-distortion Model Research Articles

Generalized Nash Bargaining Solution to Rate Control Optimization for Spatial Scalable Video Coding.

Rate control (RC) optimization is indispensable for scalable video coding (SVC) with respect to bitstream storage and video streaming usage. From the perspective of centralized resource allocation optimization, the inner-layer bit allocation problem is similar to the bargaining problem. Therefore, bargaining game theory can be employed to improve the RC performance for spatial SVC. In this paper, we propose a bargaining game based one-pass RC scheme for spatial H.264/SVC. In each spatial layer (SL), the encoding constraints, such as bit rates, buffer size are jointly modeled as resources in the inner-layer bit allocation bargaining game. The modified rate-distortion (R-D) model incorporated with the inter-layer coding information is investigated. Then the generalized Nash bargaining solution (NBS) is employed to achieve an optimal bit allocation solution. The bandwidth is allocated to the frames from the generalized NBS adaptively based on their own bargaining powers. Experimental results demonstrate that the proposed rate control algorithm achieves appealing image quality improvement and buffer smoothness. The average mismatch of our proposed algorithm is within the range of 0:19%2:63%.

Dual Cauchy rate-distortion model for video coding

A dual Cauchy rate-distortion model is proposed for video coding. In our approach, the coefficient distribution of the integer transform is first studied. Then, based on the observation that the rate-distortion model of the luminance and that of the chrominance can be well expressed by separate Cauchy functions, a dual Cauchy rate-distortion model is presented. Furthermore, the simplified rate-distortion formulas are deduced to reduce the computational complexity of the proposed model without losing the accuracy. Experimental results have shown that the proposed model is better able to approximate the actual rate-distortion curve for various sequences with different motion activities.

Delay—Power-Rate-Distortion Model for Wireless Video Communication Under Delay and Energy Constraints

Smart mobile phones are capable of performing video coding and streaming over wireless networks, but are often constrained by the end-to-end delay requirement and energy supply. To achieve optimal performance under the delay and energy constraints, in this paper we extend the traditional rate-distortion (R-D) model and the previously proposed delay R-D model to a novel delay-power-rate-distortion (d-P-R-D) model by including another two dimensions (the encoding time and encoder power consumption), which quantifies the relationship among source encoding delay, rate, distortion, and power consumption for IPPPP coding mode in H.264/AVC. We have verified the accuracy of our proposed d-P-R-D model through experiments. Based on the proposed d-P-R-D model, we develop a novel rate-control (RC) algorithm, which minimizes the encoding distortion under the constraints of rate, delay, and power. The experimental results demonstrate the superiority of the proposed RC algorithm over the existing scheme. Therefore, the d-P-R-D model and the model-based RC provide a theoretical basis and a practical guideline for the cross-layer system design and performance optimization in wireless video communication under delay and energy constraints.

An Effective Image Coding Method using Lattice Vector Quantization in Wavelet Domain

As the digital information must be stored and recovered in an effective ways, it is necessary to compress data in image coding, wavelet transform and lattice vector quantization are adopted in this paper to improve the compression effective of image coding. We first propose the two dimensional spatial wavelet decomposition of image, and then we present lattice Vector Quantization coding scheme for each image subband, lattice vector quantization can make full use of the correlation between the image wavelet coefficients to remove the information redundancy, and the coding method of lattice quantization can be effective because of applying the symmetries of the lattice. The establishment of rate distortion (RD) model suitable for lattice vector quantization of wavelet image coder is also important for image compression, study shows that the RD performance for the spatial subbands are fitted by an exponential form theoretical model, this yields an analytical solution to the bit rate distribution issue, we explore an effective rate control scheme by using the lagrangian optimization method to distribute the bit rate for the spatial subbands. The experimental results show that the proposed algorithm can achieve better compressing effect with minimum loss.

An efficient reversible data hiding scheme using prediction and optimal side information selection

In this paper, we present an efficient histogram shifting (HS) based reversible data hiding scheme for copyright protection of multimedia. Firstly, an improved HS based multi-layer embedding process for rhombus prediction is employed by introducing a control parameter to explore the correlation of prediction errors. A rate-distortion model for HS embedding is then developed for optimal side information selection, which is especially suitable for low payload reversible data hiding when only a single layer embedding is required. Finally, a modified location map is constructed to facilitate the compression of location map and further increase the embedding capacity. Compared with similar schemes, experimental results demonstrate the superior performance of the proposed scheme in the terms of embedding capacity and stego-image quality.

Joint Source-Channel Coding With Unequal Protection For Real-Time Scalable Video Transmission

In real-time video transmission, the distortion of video content may be caused by video compression in source coding and packets loss in transmission. Meanwhile the source coding distortion and transmission distortion are often mutually affected. There is a fundamental tradeoff between them for achieving the best video transmission quality. In order to make wise use of network resources, this paper proposes a video transmission scheme in which the source coding distortion and transmission distortion to the video quality are formulated and fountain code is used as the channel coding for unequal protection in scalable video transmission. The network packet loss and the characteristic of scalable video are quantitated in our proposed rate distortion model, which formulates the real-time video transmission system in a bandwidth limited network. We introduce a computerized algorithm. The computerized algorithm will determine the optimal source rate of the video coding and the optimal redundancy amount assigned...

Cross-Layer Framework for Multiuser Real Time H.264/AVC Video Encoding and Transmission over Block Fading MIMO Channels Using Outage Probability

We present a framework for cross-layer optimized real time multiuser encoding of video using a single layer H.264/AVC and transmission over MIMO wireless channels. In the proposed cross-layer adaptation, the channel of every user is characterized by the probability density function of its channel mutual information and the performance of the H.264/AVC encoder is modeled by a rate distortion model that takes into account the channel errors. These models are used during the resource allocation of the available slots in a TDMA MIMO communication system with capacity achieving channel codes. This framework allows for adaptation to the statistics of the wireless channel and to the available resources in the system and utilization of the multiuser diversity of the transmitted video sequences. We show the effectiveness of the proposed framework for video transmission over Rayleigh MIMO block fading channels, when channel distribution information is available at the transmitter.

Applying Game Theory to Rate Control Optimization for Hierarchical B-Pictures

The hierarchical B-picture structure has been widely applied for its scalability and coding efficiency. The bit allocation problem among frames in different temporal layers can be modeled as a multi-objective optimization among multiple players, which is similar to the bargaining problem. In this paper, we propose a bargaining game theory based frame-level bit allocation and rate control algorithm for hierarchical B-picture structure. First, the bit allocation problem among frames that belong to different temporal layers is modeled as a bargaining game, according to the efficiency and fairness requirement of sharing the available bandwidth resources. Second, the dependency relationship between different temporal layers and linear rate distortion model are employed to define the utility function in the bargaining game. Finally, the bandwidth is allocated for the frames based on the nash bargaining solution. Experimental results demonstrate that the proposed algorithm achieves better performance on bit rate accuracy, coding efficiency and fairness, as compared to other benchmark one-pass rate control algorithms.

Joint Bit Allocation and Rate Control for Coding Multi-View Video Plus Depth Based 3D Video

In three-dimensional (3D) video coding, distortion in texture video and depth maps can all affect the quality of the synthesized virtual views. Therefore, under the total bitrate constraint, effective bit allocation between texture and depth information is very important for 3D video coding. In this paper, the major technical contribution is to formulate view synthesis quality for optimal resource allocation in 3D video coding, since such quality is what that matters most to the ultimate user (i.e., the viewer) of the system; to be more specific, a new joint bit allocation and rate control method for multi-view video plus depth (MVD) based 3D video coding is proposed accordingly. We firstly derive a view synthesis distortion model to characterize the effect of coding distortion of texture video and depth maps on the synthesized virtual views. Based on this model, we derive a rate-distortion model to characterize the relationship between the bitrate and the view synthesis distortion, and the optimal bitrate ratio between texture and depth is established adaptively by solving the associated optimization problem. Finally, the rate control algorithm is performed on view level, texture/depth level and frame level. Experimental results show that compared with other methods, the proposed bit allocation method obtains higher performance of view synthesis. Moreover, the proposed rate control method can accurately control the bitrate to satisfy the total bitrate constraint.

Rate-Distortion Model Based Bit Allocation for 3-D Facial Compression Using Geometry Video

With the extensive applications of 3-D multimedia technology, 3-D content compression has been an important issue, which ensures its smooth transmission on the network with constrained bandwidth. In this letter, we propose a new compression framework for dynamic 3-D facial expressions. Taking advantage of the near-isometric property of human facial expressions, we parameterize the dynamic 3-D faces into an expression-invariant canonical domain, which naturally generates 2-D geometry videos and allows us to apply the well-studied video compression techniques. Due to the difference from natural videos, each dimension (i.e., X, Y and Z, respectively) of the geometry video is regarded as a video sequence and encoded separately. Meanwhile, a model-based joint bit allocation scheme is designed to allocate reasonable bitrate to each dimension by detailed analysis of rate-distortion model for geometry videos, to obtain optimal results under given target bitrate. Experimental results show that up to 25% improvement in terms of bitrate reduction can be achieved, compared to existing algorithms.

Rate-distortion based reference viewpoints selection for multi-view video plus depth coding

For multi-view video plus depth (MVD) coding in 3D video (3DV) applications, texture videos and depth maps of a few reference viewpoints should be compressed and transmitted. The other intermediate virtual viewpoints are synthesized by depth-image-based rendering algorithm. The videos displayed for terminal users include the decoded reference viewpoints and the synthesized virtual viewpoints. Under a given bit rate constraint, how to choose the optimal reference viewpoints setting to obtain the best video quality of all display viewpoints is an important research issue. This paper proposes a rate distortion model based algorithm to obtain the optimal reference viewpoints selection. First, the impacts of the reference viewpoints setting on the entire quality of all display viewpoints is investigated, and then a quadratic distortion model for all display viewpoints is derived. Based on this distortion model, the optimal viewpoints selection problem is solved by computing a few model parameters. Experimental results demonstrate that the proposed distortion model estimates the actual distortion of all display viewpoints with high accuracy, and the proposed reference viewpoints selection method achieves almost the same rate distortion performance as compared to the full search method with a very low computational cost.

Information-theoretic assessment of on-board near-lossless compression of hyperspectral data

A rate-distortion model to measure the impact of near-lossless compression of raw data, that is, compression with user-defined maximum absolute error, on the information available once the compressed data have been received and decompressed is proposed. Such a model requires the original uncompressed raw data and their measured noise variances. Advanced near-lossless methods are exploited only to measure the entropy of the datasets but are not required for on-board compression. In substance, the acquired raw data are regarded as a noisy realization of a noise-free spectral information source. The useful spectral information at the decoder is the mutual information between the unknown ideal source and the decoded source, which is affected by both instrument noise and compression-induced distortion. Experiments on simulated noisy images, in which the noise-free source and the noise realization are exactly known, show the trend of spectral information versus compression distortion, which in turn is related to the coded bit rate or equivalently to the compression ratio through the rate-distortion characteristic of the encoder used on satellite. Preliminary experiments on airborne visible infrared imaging spectrometer (AVIRIS) 2006 Yellowstone sequences match the trends of the simulations. The main conclusion that can be drawn is that the noisier the dataset, the lower the CR that can be tolerated, in order to save a prefixed amount of spectral information.

Correlation-Aware Packet Scheduling in Multi-Camera Networks

In multiview applications, multiple cameras acquire the same scene from different viewpoints and generally produce correlated video streams. This results in large amounts of highly redundant data. In order to save resources, it is critical to handle properly this correlation during encoding and transmission of the multiview data. In this work, we propose a correlation-aware packet scheduling algorithm for multi-camera networks, where information from all cameras are transmitted over a bottleneck channel to clients that reconstruct the multiview images. The scheduling algorithm relies on a new rate-distortion model that captures the importance of each view in the scene reconstruction. We propose a problem formulation for the optimization of the packet scheduling policies, which adapt to variations in the scene content. Then, we design a low complexity scheduling algorithm based on a trellis search that selects the subset of candidate packets to be transmitted towards effective multiview reconstruction at clients. Extensive simulation results confirm the gain of our scheduling algorithm when inter-source correlation information is used in the scheduler, compared to scheduling policies with no information about the correlation or non-adaptive scheduling policies. We finally show that increasing the optimization horizon in the packet scheduling algorithm improves the transmission performance, especially in scenarios where the level of correlation rapidly varies with time.

Transmission Control for Compressive Sensing Video over Wireless Channel

In this paper, we consider a wireless sensor node monitoring the environment and it is equipped with a compressive-sensing based, single-pixel image camera and other sensors such as temperature and humidity sensors. The wireless node needs to send the data out in a timely and energy efficient way. This transmission control problem is challenging in that we need to jointly consider perceived video quality, quality variation, power consumption and transmission delay requirements, and the wireless channel uncertainty. We address the above issues by first building a rate-distortion model for compressive sensing video. Then we formulate the deterministic and stochastic optimization problems and design the transmission control algorithm which jointly performs rate control, scheduling and power control. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed transmission control algorithm.

Performance Analysis For Dct-Based Coded Image Communication In Wireless Multimedia Sensor Networks

Abstract The objective of this paper is to study the image communication behavior of a wireless video sensor, and analyze its performance under resource constrained wireless multimedia sensor networks. Energy consumption and rate distortion model of DCT-based coded image compression and transmission is developed. Based on energy consumption and rate distortion model proposed, resource allocation is optimized with limited energy and bandwidth. Number of DCT coefficient and step size of quantization table is adapted according to the activity of monitoring scene, and then the energy consumption will be minimized. Simulations results are conducted to show the performance of our work. The proposed scheme dramatically reduces image compression and transmission energy consumption under expected image distortion and transmission rate.

실시간 영상 부호화를 위한 H.264/AVC의 비트율 제어 하드웨어 설계

In this paper, the hardware design of rate control for real-time video encoded is proposed. In the proposed method, a quadratic rate distortion model with high-computational complexity is not used when quantization parameter values are being decided. Instead, for low-computational complexity, average complexity weight values of frames are used to calculate QP. For high speed and low computational prediction, the MAD is predicted based on the coded basic unit, using spacial and temporal correlation in sequences. The rate control is designed with the hardware for fast QP decision. In the proposed method, a quadratic rate distortion model with high-computational complexity is not used when quantization parameter values are being decided. Instead, for low-computational complexity, average complexity weight values of frames are used to calculate QP. In addition, the rate control is designed with the hardware for fast QP decision. The execution cycle and gate count of the proposed architecture were reduced about 65% and 85% respectively compared with those of previous architecture. The proposed RC was implemented using Verilog HDL and synthesized with UMC standard cell library. The synthesis result shows that the gate count of the architecture is about 19.1k with 108MHz clock frequency.

Rate-distortion optimised quantisation for direct current coefficients of Wyner–Ziv frame in unidirectional distributed video coding

This study presents a rate-distortion (RD) optimised quantisation algorithm for direct current (DC) coefficients of the Wyner–Ziv (WZ) frames in unidirectional distributed video coding. As the side information (SI) could be viewed as a ‘corrupted’ version of the original WZ frame, the correlation noise (WZ-SI) can be interpreted as a virtual channel with an error pattern. In this study, the distortion caused by virtual channel errors, besides quantisation errors, is analysed emphatically for unidirectional WZ video coding. In their presented quantisation algorithm, a novel RD model is developed to find out the optimal quantisation step size, in which the quantisation distortion and virtual channel error distortion together with the encoding rate are formulated using the quantisation step size without feedback channels. Then the RD optimal step size for DC coefficients can be solved through minimising the RD cost. In simulations, the comparison of RD performance between their proposed algorithm and the quantisation method used in distributed coding for video services (DISCOVER) is presented. Experimental results show that the proposed RD optimised quantisation for DC coefficients can improve the average peak signal-to-noise ratio of WZ frames by 0.4–1.2 dB for quarter common intermediate format (QCIF) sequences and 0.2–0.4 dB for common intermediate format (CIF), at the expense of increasing the encoding complexity slightly.

Predictive Encoder and Buffer Control for Statistical Multiplexing of Multimedia Contents

Statistical multiplexing of video contents aims at transmitting several variable bit rate (VBR) encoded video streams over a band-limited channel. Rate-distortion (RD) models for the encoded streams are often used to control the video encoders. Buffering at the output of encoders is one of the several techniques used to smooth out the fluctuating bit rate of compressed video due to variations in the activity of video contents. In this paper, a statistical multiplexer is proposed where a closed-loop control of both video encoders and buffers is performed jointly. First, a predictive joint video encoder controller accounting for minimum quality, fairness, and smoothness constraints is considered. Second, all buffers are controlled simultaneously to regulate the buffering delays. This delay is adjusted according to a reference delay constraint. The main idea is to update the encoding rate for each video unit according to the average level of the buffers, to maximize the quality of each program and effectively use the available channel rate. Simulation results show that the proposed scheme yields a smooth and fair video quality among programs thanks to the predictive control. A similar buffering delay for all programs and an efficient use of the available channel rate are ensured thanks to the buffer management and to the predictive closed-loop control.

Single-Pass Rate Control With Texture and Non-Texture Rate-Distortion Models

One of the challenges in video rate control lies in determining a quantization parameter (Qp) that will be used for both the rate-distortion (R-D) optimization process and the quantization of transform coefficients. In this paper, we attempt to achieve effective rate control with a different approach. By modeling the relationships of distortion, texture bits, non-texture bits, and Qp, we derive the Qp required for both R-D optimization and quantization through Lagrangian optimization. From experiments with several video sequences, we found that our rate control scheme is capable of effective rate control with only a few model updates during encoding. The proposed rate control scheme adapts quickly to the characteristics of the source data and is particularly effective at controlling the rate of videos with high and unpredictable motion content.

Novel rate control scheme for intra frame video coding with exponential rate–distortion model on H.264/AVC

Rate control regulates the output bit rate of a video encoder in order to obtain optimum visual quality within the available network bandwidth and to maintain buffer fullness within a specified tolerance range. Due to the benefits of intra-only encoding, such as less computational cost and less latency, it has been more and more widely used. In this paper, we propose an accurate intra-only rate control scheme for H.264/AVC, which includes a novel complexity measurement and a new rate–distortion (R–D) model. We also propose a linear rate–complexity model which takes the intercept into consideration to reduce the estimation error. The proposed R–D model is integrated by the linear rate–complexity model and an exponential rate–quantization model. Based on theoretical analysis and experimental validation, the proposed scheme has high bits prediction precision, and it can also accurately handle buffer fullness. Compared with JVT-W042, our algorithm achieves higher average PSNR and improves the coding quality up to 0.35dB.