Rate-distortion analysis for light field coding and streaming

A theoretical framework to analyze the rate-distortion performance of a light field coding and streaming system is proposed. This framework takes into account the statistical properties of the light field images, the accuracy of the geometry information used in disparity compensation, and the prediction dependency structure or transform used to exploit correlation among views. Using this framework, the effect that various parameters have on compression efficiency is studied. The framework reveals that the efficiency gains from more accurate geometry, increase as correlation between images increases. The coding gains due to prediction suggested by the framework match those observed from experimental results. This framework is also used to study the performance of light field streaming by deriving a view-trajectory-dependent rate-distortion function. Simulation results show that the streaming results depend both the prediction structure and the viewing trajectory. For instance, independent coding of images gives the best streaming performance for certain view trajectories. These and other trends described by the simulation results agree qualitatively with actual experimental streaming results.     

率失真优化的压缩感知图像编码

针对基于压缩感知的图像编码系统,分析了系统中编码参数和码率以及失真的关系,在此基础上提出了基于压缩感知的图像编码系统的码率-失真模型.根据所提模型设计了率失真优化的压缩感知图像编码算法.在给定码率的条件下,优化编码参数,使得编码器失真最小.算法在Matlab的编码平台上进行了仿真和实验,结果证明提出的码率-失真模型能够很好地拟合实际率失真曲线,并且基于该模型的率失真优化算法有效的提高了压缩感知图像编码系统的性能.     

Rate-distortion speech coding with a minimum discrimination information distortion measure

An information theory approach to the theory and practice of linear predictive coded (LPC) speech compression systems is developed. It is shown that a traditional LPC system can be viewed as a minimum distortion or nearest-neighbor system where the distortion measure is a minimum discrimination information between a speech process model and an observed frame of actual speech. This distortion measure is used in an algorithm for computer-aided design of block source codes subject to a fidelity criterion to obtain a 750-bits/s speech compression system that resembles an LPC system but has a much lower rate, a larger memory requirement, and requires no on-line LPC analysis. Quantitative and informal subjective comparisons are made among our system and LPC systems.     

高效率的多视点视频编码预测结构*

预测结构是多视点视频编码(Multi-View Video Coding,MVC)研究的主要内容之一。MVC目前采用HHI(Heinrich-Hertz-Institute)提出的分层次B帧预测结构(HBP),比联播预测结构获得了更好的压缩效率。分析了多种预测结构,并针对平行摄像机采集的多视点视频序列,提出了一种新的预测结构AS_EIPP,该结构充分利用相邻视点间的相关性和多参考帧模式,进一步提高了压缩效率。在多视点视频软件测试平台JMVC8.3上进行验证,实验结果表明:新的预测结构在保证重建视频质量基本不变的前提下,压缩效率比HBP预测结构提高了1%～4%。     

Depth-based direct mode for multiview video coding

Multiview video plus depth sequence is considered as an efficient 3D video format for supporting advanced stereoscopic and auto-stereoscopic multiview displays. In order to encode this video format, several modes are commonly employed with rate distortion optimization technique. Specifically, direct mode is an efficient mode to encode homogeneous or stationary regions without encoding any additional motion information. However, in the format, the conventional direct mode causes inaccuracy of motion parameters, i.e., a motion vector and a reference index. Thus, we propose a new method for deriving motion parameters of direct mode, which settles the inaccuracy problem, based on depth information and priority of neighboring blocks determined by their relative position. The proposed direct mode achieves an improvement in coding performance when compared with two state-of-the-art direct modes for multiview video coding. The experimental results show that the proposed method yields average bitrate savings of 4.6%, up to 13.7% in terms of the Bjontegaard Delta metric.     

Depth perceptual region-of-interest based multiview video coding

MultiView Video (MVV) has attracted considerable attention recently since it is capable of providing users with three-dimensional perception and interactive functionalities. However, these MVV data require large mount of storage and bandwidth in network transmission. In this paper, we present a novel Depth Perceptual Region-Of-Interest (DP-ROI) based Multiview Video Coding (RMVC) scheme to extensively improve data compression efficiency by exploiting redundancies in depth perception. Firstly, we define DP-ROI according to the three-dimensional depth sensation of human visual system. Then, a framework of RMVC is developed to improve compression efficiency by properly segmenting the MVV into different macroblock wise DP-ROIs and encoding them separately. And then, we propose three fast depth based DP-ROI extraction and tracking algorithms by jointly using motion, texture, depth as well as previous extracted DP-ROIs. Finally, on the basis of the extracted DP-ROI, bit allocation optimization model is proposed to allocate more bits on DP-ROIs for high image quality and fewer bits on background regions for high compression ratio. Experimental results show that the presented RMVC scheme achieves significant coding gains at high rate while comparing with original joint multiview video model. To be specific, up to 14.22–23.32% bit-rate are saved while 0.16–0.68 dB coding gains are achieved in DP-ROIs at the cost of the image quality degradation in background.     

多视点视频编码的研究现状及其展望

阐述了多视点视频编码(MVC)的主要研究问题.其中首先介绍了MVC的体系结构和发展过程;然后详细讨论了MVC的研究内容,包括预测结构、提高MVC编码效率的技术和高层语法;最后在总结MVC研究现状的基础上,提出了MVC在3D视频应用中的研究思路.     

A polygon soup representation for multiview coding

This paper presents a polygon soup representation for multiview data. Starting from a sequence of multiview video plus depth (MVD) data, the proposed quad-based representation takes into account, in a unified manner, different issues such as compactness, compression, and intermediate view synthesis. The representation is extracted from MVD data in two steps. First, a set of 3D quads is extracted thanks to quadtree decomposition performed on depth maps. Second, a selective elimination of the quads is performed in order to reduce inter-view redundancies and thus provide a compact representation. Moreover, the proposed methodology for extracting the representation allows to reduce ghosting artifacts. Finally, an adapted compression technique is proposed that limits coding artifacts. The results presented on two real sequences show that the proposed representation provides a good trade-off between rendering quality and data compactness.     

Rate-distortion optimized layered coding of high dynamic range videos

An efficient algorithm to compress high dynamic range (HDR) videos into layered bitstreams is proposed in this work. First, we separate an HDR video sequence into a tone-mapped low dynamic range (LDR) sequence and a ratio sequence, which represents ratios between HDR and LDR pixel values. Then, we encode the LDR and ratio sequences to maximize the rate-distortion (R–D) performance by extending the standard H.264/AVC codec. Specifically, we estimate the distortion of the HDR sequence from those of the LDR sequence and the ratio sequence, and then allocate a limited bit budget to the LDR sequence and the ratio sequence efficiently to maximize the qualities of both LDR and HDR sequences. Conventional LDR devices use only the LDR stream, whereas HDR devices reconstruct the HDR video from the LDR and ratio streams. Simulation results show that the proposed algorithm provides significantly better R-D performance than conventional HDR video coding techniques.     

Joint depth-motion dense estimation for multiview video coding

The multiview video coding (MVC) extension of H.264/MPEG-4 AVC [1] is one of the most promising visual encoders for three-dimensional television and free viewpoint video applications. In this paper, we propose a joint dense motion/disparity estimation algorithm, designed to replace the classical temporal/inter-view unit within MVC, which uses a block-based motion/disparity estimation. The motion vector fields and the disparity vector fields are therefore simultaneously derived using the stereo-motion consistency constraint in a set theoretic convex optimization framework. The obtained displacement vector fields are then jointly segmented by minimizing a rate-distortion cost function, in line with the multiple reference frame strategy used in H.264/MPEG-4 AVC. Experimental results demonstrate the benefits of the proposed method compared to the separated dense estimation scheme or the block-based estimation technique.     

Rate-distortion driven decoder-side bitplane mode decision for distributed video coding

Distributed video coding (DVC) features simple encoders but complex decoders, which lies in contrast to conventional video compression solutions such as H.264/AVC. This shift in complexity is realized by performing motion estimation at the decoder side instead of at the encoder, which brings a number of problems that need to be dealt with. One of these problems is that, while employing different coding modes yields significant coding gains in classical video compression systems, it is still difficult to fully exploit this in DVC without increasing the complexity at the encoder side. Therefore, in this paper, instead of using an encoder-side approach, techniques for decoder-side mode decision are proposed. A rate-distortion model is derived that takes into account the position of the side information in the quantization bin. This model is then used to perform mode decision at the coefficient level and bitplane level. Average rate gains of 13–28% over the state-of-the-art DISCOVER codec are reported, for a GOP of size four, for several test sequences.     

联合彩色信息的多视点深度视频视差矢量预测

多视点加深度(MVD)格式可以利用虚拟视点绘制技术生成任意视点的视频,能高效地向观看者提供立体感知。由于MVD中的深度视频与对应的彩色视频采集于同一场景,具有高度的相关性。因此,深度视频可以利用已编码的彩色信息辅助编码。提出一种联合彩色信息的多视点深度视频视差矢量预测方法。该方法首先获得当前编码深度块对应位置的彩色块,提取彩色块预测得到的视差矢量作为深度块的一个候选视差矢量。然后,利用深度块信息计算得到另一个候选视差矢量。最后,对两个候选视差矢量通过计算下采样均方差,选择更精确的一个作为当前深度块的视差矢量预测值。实验结果表明,所提出的方法性能优于3D-HEVC编码平台HTM。     

A unified rate-distortion analysis framework for transform coding: a summary

In our previous work, we have developed a rate-distortion (R-D) modeling framework H.263 video coding by introducing the new concepts of characteristic rate curves and rate curve decomposition. In this paper, we further show it is a unified R-D analysis framework for all typical image/video transform coding systems, such as EZW, SPIHT and JPEG image coding; MPEG-2, H.263, and MPEG-4 video coding. Based on this framework, a unified R-D estimation and control algorithm is proposed for all typical transform coding systems. We have also provided a theoretical justification for the unique properties of the characteristic rate curves. A linear rate regulation scheme is designed to further improve the estimation accuracy and robustness, as well as to reduce the computational complexity of the R-D estimation algorithm. Our extensive experimental results show that with the proposed algorithm, we can accurately estimate the R-D functions and robustly control the output bit rate or picture quality of the image/video encoder.     

Toward a unified framework for modeling and analysis of diversity in joint source-channel coding

The study of joint source-channel coding (JSCC) systems faces one major challenge in obtaining an analytical expression for the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve. In this paper, for certain multimedia systems using practical source and channel codes in a JSCC bit rate allocation design, the D-SNR curve is shown to be well approximated by a set of carefully selected points where the relative contribution of channel errors to end-to-end distortion is small. This approach has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation for which it is shown that the D-SNR function is approximately linear in log-log scales. A unified framework for the modeling, analysis and performance measurement of these systems is proposed by considering a view of diversity more general than its usual interpretation. This view extends that of diversity to include redundant information so coding and diversity gain are still used to characterize performance. Furthermore, the proposed approach is applied to study issues arising from using practical source and channel codes, including the effects on performance of channel codes of different strength or source codes with different compression efficiency.     

Rate-distortion modeling for multiscale binary shape coding based on Markov random fields

The purpose of this paper it to explore the relationship between the rate-distortion characteristics of multiscale binary shape and Markov random field (MRF) parameters. For coding, it is important that the input parameters that will be used to define this relationship be able to distinguish between the same shape at different scales, as well as different shapes at the same scale. We consider an MRF model, referred to as the Chien model, which accounts for high-order spatial interactions among pixels. We propose to use the statistical moments of the Chien model as input to a neural network to accurately predict the rate and distortion of the binary shape when coded at various scales.     

低复杂度的多视点视频编码宏块模式决策算法

为了降低多视点视频编码(MVC)的计算复杂度,提出了一种基于全局-局部率失真代价的低复杂度宏块模式决策算法。首先根据宏块候选模式的块尺寸和率失真代价特点,将所有候选模式分为大尺寸模式(Skip/Direct、Inter16×16和Intra16×16)和小尺寸模式(Inter16×8、Inter8×16、Inter8×8、Intra8×8和Intra4×4);接着统计已编码帧中这两类宏块模式的平均率失真代价,并利用这些平均率失真代价计算当前帧宏块模式决策的全局率失真代价;最后利用得到的全局率失真代价,并结合当前宏块已估计模式的局部率失真代价和空间邻近宏块的模式信息提前终止模式决策,具体包括对大尺寸宏块模式进行提前判定以及对小尺寸候选模式进行逐级选择。实验结果表明:与MVC参考代码中的全搜索模式决策算法相比,本文算法在时域预测视点和视点域预测视点上分别节省了74%和82%的平均编码时间,同时保持了良好的编码率失真性能;与现有模式决策快速算法相比,本文算法降低了更多的编码时间,并具有更好的编码率失真性能。     

基于转移概率的多视点视频快速模式选择算法

针对多视点视频编码(MVC)中部分大宏块模式(SKI P/DIRECT模式,帧间16×16模式)相对于其它模式的计算复杂 度低,并且在编码所确定的最优模式中占有相当高比重的特点,本文提出一种基于转移概率 的多视点视频 快速模式选择算法。首先根据多视点视频当前编码宏块对应时间和视点间宏块及周围宏块的 位置几何关系, 建立宏块模式参考模型;其次比较参考模型中模式的时间相似度和视点间相似度;最后计算 模式之间的转 移概率,确定提前结束大宏块模式选择过程的阈值。实验结果表明,本文所提出的快速算法 平均节约MVC时间80.93%,编码质量平均下降0.04dB,码率平均增加0.27%。     

Disparity field and depth map coding for multiview 3D image generation

In the present paper techniques are examined for the coding of the depth map and disparity fields for stereo or multiview image communication applications. It is assumed that both the left and right channels of the multiview image sequence are coded using block- or object-based methods. A dynamic programming algorithm is used to estimate a disparity field between each stereo image pair. Depth is then estimated and occlusions are optionally detected, based on the estimated disparity fields. Spatial interpolation techniques are examined based on the disparity/depth information and the detection of occluded regions using either stereoscopic or trinocular camera configurations. It is seen that the presence of a third camera at the transmitter site improves the estimation of disparities, the detection of occlusions and the accuracy of the resulting spatial interpolation at the receiver. Various disparity field and depth map coding techniques are then proposed and evaluated, with emphasis given to the quality of the resulting intermediate images at the receiver site. Block-based and wireframe modeling techniques are examined for the coding of isolated depth or disparity map information. Further, 2D and 3D motion compensation techniques are evaluated for the coding of sequences of depth or disparity maps. The motion fields needed may be available as a byproduct of block-based or object-based coding of the intensity images. Experimental results are given for the evaluation of the performance of the proposed coding and spatial interpolation methods.     

Optimising inter-view prediction structure for multiview video coding with minimum spanning tree

A new systematic method to construct a near-optimal inter-view prediction structure for multiview video coding is proposed based on the directed minimum spanning tree of inter-view prediction cost graph. The method is applicable to arbitrary irregular and dynamic changing camera arrangements. Results show that the generated structure achieves better compression efficiency than the reference structure of the joint multiview video model.