Effective computation-aware algorithm by inter-layer motion analysis for scalable video coding

Scalable video coding incorporated with computation-aware ability achieves quality as well as being computation scalable. This paper presents a computation-aware algorithm for scalable video coding with spatial/quality scalability aiming for the best trade-off between rate distortion performance and computational consumption. We first observe and analyze and then establish a model for the motion vector difference relationship between the scalable base and enhancement layers. By using the modeling results, a linear algorithm for computation distribution is thus proposed to allocate the computation for each macroblock in the enhancement layer. In addition, the rate distortion costs of the base layer are also taken into account for the computation allocation process in order to further improve the coding performance. The simulation results demonstrate that our proposed computation-aware algorithm not only accomplishes better rate distortion performance than other works under the same computational constraints, but also achieves less computation necessities.     

Lagrange multiplier selection in wavelet-based scalable video coding for quality scalability

In this paper, a method for Lagrange multiplier selection is proposed in the context of rate-distortion optimisation for wavelet-based scalable video coding targeting quality scalability. Despite the prevalence of the conventional method for Lagrange multiplier selection in hybrid video coding, the underlying formulation is not applicable to wavelet-based scalable video coding. To address the inherent challenges, a thorough analysis of the rate-distortion models for transform video coding is provided with regard to low and middle-to-high bit-rates, respectively. Based on the analysis, the models are consolidated according to experimental observations and the consolidated rate-distortion models serve as the basis for the derivation of the Lagrange multiplier. Considering the influence of the open-loop prediction structure on the rate-distortion performance, the Lagrange multiplier is initially derived for a single-targeted bit-rate. Moreover, the method for Lagrange multiplier selection in scalable video coding aiming at multiple-targeted bit-rates is proposed in a general sense of bit-rate range, varying from low to high bit-rates, building on the initially derived Lagrange multiplier for a single-targeted bit-rate. The proposed Lagrange multiplier is content adaptive and well suited for wavelet-based scalable video coding where quantisation steps are unavailable. Detailed performance evaluation of the proposed method for wavelet-based scalable video coding is provided with regard to a given targeted bit-rate and multiple-targeted bit-rates, respectively. The experimental results have demonstrated the effectiveness of the proposed Lagrange multiplier for rate-distortion optimisation considering quality scalability in wavelet-based scalable video coding.     

An efficient scalable intra coding algorithm for spatial scalability in enhancement layer

Scalable video coding (SVC) is attractive due to the capability of reconstructing lower resolution or lower quality signals from partial bit streams, which allows for simple solutions adaptted to network and terminal capabilities. This article addresses the spatial scalability of SVC and proposes an efficient H.264-based scalable intra coding algorithm. In comparison with precious single layer intra prediction (SLIP) method, the proposed algorithm aims to improve the intra coding performance of the enhancement layer by a new inter layer intra prediction (ILIP) method. The main idea of ILIP is that up-sampled and reconstructed pixels of the base layer are very useful to predict and encode those pixels of the enhancement layer, especially when those neighbouring pixels are not available. Experimental results show that the peak signal to noise ratio (PSNR) data of luminance component of encoded frames are improved, and both bit-rates and computation complexity are maintained very well. For sequence Football, the average increase of PSNR is up to 0.21?dB, while for Foreman and Bus, they are 0.14?dB and 0.17?dB, respectively.     

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 (Q_p) 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 Q_p 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 Q_p 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.     

Sub-band coding with adaptive bit allocation

The paper presents an efficient method for speech encoding which is based on the well known idea of sub-band coding. Typically, the frequency range from 0.3 kc/s to 3.4 kc/s is split into four sub-bands, and the sub-band signals are encoded separately with different accuracies by means of familiar PCM techniques. An adaptive bit allocation scheme is introduced here, in order to replace the usual form of a fixed distribution of the bit rate among the sub-bands. Listening tests have shown that by these means the bit rate can be reduced by more than 2.5 kb/s without degrading speech quality. Accordingly, highly intelligible reproduction of speech is possible at bit rates below 7 kb/s.     

Adaptive packet scheduling for scalable video streaming with network coding

Over the last decade, the emergence of new multimedia devices has motivated the research on efficient media streaming mechanisms that adapt to dynamic network conditions and heterogeneous devices’ capabilities. Network coding as a rateless code has been applied to collaborative media streaming applications and brings substantial improvements regarding throughput and delay. However, little attention has been given to the recoverability of encoded data, especially for the streaming with a strict deadline. This in turn leads to severe quality of experience. In this paper, we solve the unrecoverable transmission by proposing a multi-generation packet scheduling problem, which is treated as a video quality maximization problem and solved using dynamic programming algorithm. Experimental results confirm that the proposed algorithm brings better data recoverability and better quality of service in terms of video quality, delivery ratio, lower redundancy rate under different network sizes.     

基于零块分析的高效视频编码通信

为了实现高清、超高清视频实时编码通信传输, 针对高效视频编码(HEVC)帧间编码计算复杂度过高的问题,根据图像的文理复杂度和 编码单元的零块统计特征,提出一种新的HEVC快速帧间模式判决算法。根据Merge模式下 整单元一分为四的4个子编码单元纹 理相似度确定是否提前终止编码单元(CU)划分,同时利用帧间2N×2N预测模式下零系数与非零系数分布的区域统计特征,选择符合零块分 布特征的最佳预测单元(PU)模式。实验结果表明,在低延迟B(LDB,low-delay B)和随机访 问(RA,random access)配置条件下,提出的算法在保持编码 性能基本不变的情况下,HEVC帧间预测编码时间分别平均减少了60.2%与59.4%。     

Motion-compensated DCT temporal filters for efficient spatio-temporal scalable video coding

Although most of the proposals for implementing motion-compensated temporal filtering (MCTF) schemes are based on the wavelet transform, in this paper, we propose an MCTF framework based on the discrete cosine transform (DCT). Using DCT decimation and interpolation, several temporal decomposition structures named motion-compensated DCT temporal filters (MCDCT-TF) are introduced. These structures are able to employ filters of any length with particular emphasis on 5/3 DCT and 7/4 DCT. The proposed MCDCT-TF and the two-dimensional (2D) DCT decimation technique are incorporated into H.264/AVC to provide spatio-temporal scalability. Compared with the current MCTF-based lifting schemes such as Haar, and 5/3 wavelet filters, simulation results show that the proposed MCDCT-TF utilizing longer tap DCT filters achieves a significant improvement in coding gain. The impact of odd/even group of frames, the decimation/interpolation ratios, and motion-compensated connectivity on the MCDCT-TF performance are also analyzed. Moreover, simulation results show that the performance of the presented scalable video coding is close to the single layer H.264/AVC and is slightly inferior to the temporal scalability supported in JSVM, the state-of-the-art scalable video coding standard, that gets its gain from Hierarchical B-pictures. However, our spatio-temporal coding scheme outperforms the spatio-temporal supported in JSVM even if it uses hierarchical B-pictures to improve its gain.     

可伸缩视频流的安全网络编码方案

为了使可伸缩视频流在异构网络中达到分层安全等级的目的,运用随机函数来随机化视频流各层中的部分数据流,并结合网络编码来抵御已知的明文攻击。此外,对网络编码器进行了研究,设计有序随机线性网络编码器用于可伸缩视频的传输,可以用很少的随机化操作来达到可扩展的安全等级,并降低通信开销。分析表明,所提方案可有效增加网络的吞吐率。     

适用于实时交通监控的时空可伸缩视频编码方法

提出了一种适用于视频监控的时空可伸缩编码方法。首先提出一种适用于可伸缩视频编码特点的监控算法,利用该算法将运动区域从背景中提取出来,并用模式和方向快速判别算法去掉对编码增益很小的冗余模式,基本层利用该算法进行编码,增强层利用基本层的信息预测可能的模式集合,然后进行零块预先判决,最后对最高时间级的高速运动块通过视觉门限来降低其空间冗余度。实验证明,该方法能够较大地提高编码速度和一定程度上提高压缩率,并且视觉质量损失很小。     

Frame distortion estimation for unequal error protection methods in scalable video coding (SVC)

In many multimedia applications, coded video is transmitted over error prone heterogeneous networks. Because of the predictive mechanism used in video coding, transmission error would propagate temporally and spatially and would result in significant quality losses. In order to address this problem, different error resilience methods have been proposed. One of the techniques, which is commonly used in video streaming, is unequal error protection (UEP) of scalable video coding (SVC). In this technique, different independent layers of an SVC stream are protected differently and based on their importance by using forward error correction (FEC) codes. Accurately analyzing the importance or utility of each video part is a critical component and would lead to a better protection and higher quality of the received video. Calculation of the utility is usually based on multiple decoding of sub-bitstreams and is highly computationally complex. In this work, we propose an accurate low complexity utility estimation technique that can be used in different applications. This technique estimates the utility of each network abstraction layer (NAL) by considering the error propagation to future frames. We utilize this method in an UEP framework with the scalable extension of H.264/AVC codec and it achieves almost the same performance as highly complex estimation techniques (an average loss of 0.05 dB). Furthermore, we propose a low delay version of this technique that can be used in delay constrained application. The estimation accuracy and performance of our proposed technique are studied extensively.     

面向HEVC的恰可察觉编码失真模型

为进一步提高现有视频编码技术的压缩效率及解 码重建图像的主观视觉感知质量,在现有人眼恰可 察觉失真(JND,just noticeable distortion)模型的基础上, 提出了恰可察觉编码失真(JNCD,just noticeable coding dist ortion)模型。首先,通过主观实验,对恰可察觉梯 度幅值差异(JNGD,just noticeable gradient difference)进 行了研究,分析其变化规律并建立JNGD模型。使用全变 分(TV,total variation)方法将图像分解为结构图和纹理图后,分别求 取其梯度信息得到结构梯度图和纹理梯度图, 利用JNGD模型分别滤除结构梯度图和纹理梯度图中的人眼不可察觉的梯度幅值 ;其后,分析了人眼感知对于不同 梯度幅值的编码失真敏感性,设计了梯度幅值与JNCD值的主观实验,得到两者的关系模型; 最后,考虑人眼对图 像中的边缘、平坦和纹理3类区域失真感知程度的差异性,利用滤波后的结构梯度和纹理梯 度信息将图像划分为上 述3类区域,最终建立整幅图像的JNCD模型。为验证本文提出的JNCD模型的可靠性,在高效 视频编码(HEVC)标准测试平台上进行的模型验证结果表明,在本模 型指导下的编码其解码重建 图像获得了较好的主观视觉效果,可为人眼视觉感知冗余的分析及感知编码的改 进提供依据。     

Multiview coding and error correction coding for 3D video over noisy channels

We consider the joint source–channel coding problem of stereo video transmitted over AWGN and flat Rayleigh fading channels. Multiview coding (MVC) is used to encode the source, as well as a type of spatial scalable MVC. Our goal is to minimize the total number of bits, which is the sum of the number of source bits and the number of forward error correction bits, under the constraints that the quality of the left and right views must each be greater than predetermined PSNR thresholds at the receiver. We first consider symmetric coding, for which the quality thresholds are equal. Following binocular suppression theory, we also consider asymmetric coding, for which the quality thresholds are unequal. The optimization problem is solved using both equal error protection (EEP) and a proposed unequal error protection (UEP) scheme. An estimate of the expected end-to-end distortion of the two views is formulated for a packetized MVC bitstream over a noisy channel. The UEP algorithm uses these estimates for packet rate allocation. Results for various scenarios, including non-scalable/scalable MVC, symmetric/asymmetric coding, and UEP/EEP, are provided for both AWGN and flat Rayleigh fading channels. The UEP bit savings compared to EEP are given, and the performances of different scenarios are compared for a set of stereo video sequences.     

一种适用于AVS-M的自适应快速运动估计算法

为了减小移动视频编码标准(AVS-M)中运动估计模块的复杂度,提出了一种快速、有效的块匹配运动估计算法.该算法充分利用了视频图像中运动矢量场的中心偏置特性和时空相关性,根据运动类型自适应的选择搜索起点和搜索策略,结合改进的搜索模板和高效搜索中止准则,有效地降低了运动估计的运算量.实验结果表明,该算法在保证搜索精度的同时,大大减少了搜索点数.     

Joint video/depth rate allocation for 3D video coding based on view synthesis distortion model

Joint video/depth rate allocation is an important optimization problem in 3D video coding. To address this problem, this paper proposes a distortion model to evaluate the synthesized view without access to the captured original view. The proposed distortion model is an additive model that accounts for the video-coding-induced distortion and the depth-quantization-induced distortion, as well as the inherent geometry distortion. Depth-quantization-induced distortion not only considers the warping error distortion, which is described by a piecewise linear model with the video power spectral property, but also takes into account the warping error correlation distortion between two sources reference views. Geometry distortion is approximated from that of the adjacent view synthesis. Based on the proposed distortion model, a joint rate allocation method is proposed to seek the optimal trade-off between video bit-rate and depth bit-rate for maximizing the view synthesis quality. Experimental results show that the proposed distortion model is capable of approximately estimating the actual distortion for the synthesized view, and that the proposed rate allocation method can almost achieve the identical rate allocation performance as the full-search method at less computational cost. Moreover, the proposed rate allocation method consumes less computational cost than the hierarchical-search method at high bit-rates while providing almost the equivalent rate allocation performance.