Multi-view video coding with view interpolation prediction for 2D camera arrays

An efficient compression algorithm for multi-view video sequences, which are captured by two-dimensional (2D) camera arrays, is proposed in this work. First, we propose a novel prediction structure, called three-dimensional hierarchical B prediction (3DHBP), which can efficiently reduce horizontal inter-view redundancies, vertical inter-view redundancies, and temporal redundancies in multi-view videos. Second, we develop a view interpolation scheme based on the bilateral disparity estimation. The interpolation scheme yields high quality view frames by adapting disparity estimation and compensation procedures using the information in neighboring frames. Simulation results demonstrate that the proposed multi-view video coding algorithm provides significantly better rate–distortion (R–D) performance than the conventional algorithm, by employing the 3DHBP structure and using interpolated view frames as additional reference frames.     

Very low bit-rate video coding with DFD segmentation

A video coding system for applications requiring very low bit-rate is presented. This coding scheme uses an intraframe coder for the initial frame in the video sequence and subsequent frames are coded using an interframe coding method. A wavelet-based technique is used for intraframe coding. For interframe coding, displaced frame differences (DFD) are computed and coded using a segmentation-based method wherein the displaced frame difference is segmented into active and inactive regions using morphological operators. To meet the very low bit-rate requirements, the motion vectors are processed so as to reduce their contribution to the overall bit-rate. To reduce coding artifacts, a post-processing technique is developed for use at the decoder. Coding performance of the proposed coding scheme is evaluated at 16 kbit/s and 32 kbit/s using luminance component of several typical test sequences at QCIF resolution with a frame rate 8.3 frame/s.     

多视点视频编码中的视频目标提取与视差匹配

在单通道视频目标分割算法的基础上,首先提出一种多视点视频编码中的视频目标提取方案.然后提出一种基于多级块匹配视差估计算法.应用Moravec算子对视差矢量图进行检测,提取特征视差矢量并对其进行精确度检验.若特征视差矢量不够精确,则其所在块将重新进行小范围的块匹配.若块匹配误差仍太大则将其分裂为四个子块重新匹配.与传统块匹配算法相比,新方法能获得较为精确和平滑的视差场,提高重建后的图像质量.     

Motion vector replensihment for low bit-rate video coding

A low bit-rate video codec based on motion vector replenishment is described. Motion vectors are used to update pictures at full frame rate. In addition, part of each frame is conditionally updated with a strip of interframe video data. The video data fill the remaining channel capacity not used for motion vectors. Thus under most conditions, each frame is fully updated by motion vectors and partially with interframe video data. This method has a comparable compression efficiency with that of the frame dropping method, but does not introduce any picture ‘jerkiness’. Finally the application of the proposed method to packet video networks is examined.     

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%。     

Hybrid model-and-object-based real-time conversational video coding

Bandwidth-constrained real-time conversational video communications (such as mobile teleconferencing) require video codecs with good rate-distortion characteristics at low bit-rates and modest computational complexity. While target-specific object-based and model-based coding methods have been proposed for low bit-rate conversational video coding, difficulties in generalization and high computational complexity hinder their practical utilization. In this paper, we propose a low bit-rate coding method for typical conversational video by combining two-dimensional model-based coding of face regions and object-based coding of non-face head-shoulder regions, achieving high-quality face reconstruction and low overall bit-rate with real-time encoding capability. Experiments on typical conversational test sequences confirm that, compared to other conversational video codecs, our model-and-object-based coding method offers superior rate-distortion performance at low bit-rates.     

Temporal image sequence prediction using motion field interpolation

A new method for motion-compensated temporal prediction of image sequences is proposed. Motion vector fields in natural scenes should possess two basic properties. First, the field should be smoothly varying within moving objects to compensate for nonrigid or rotational motion, and scaling of objects. Second, the field should be discontinuous along the boundaries of the objects. In the proposed method the motion vector field is modelled using finite element methods and interpolated using adaptive interpolators to satisfy the above-stated requirements. This is particularly important when only very sparse estimates of motion vector fields are available in the decoder due to bit-rate constraints limiting the amount of overhead information that can be transmitted. The proposed prediction method can be applied for low-bit-rate video coding in conventional codecs based on motion-compensated prediction and transform coding, as well as in model-based codecs. The performance of the proposed method is compared with standard motion-compensated prediction based on block matching. It is shown that for simple video telephony scenes a reduction of more than 30% in the energy of the prediction error can be achieved with an unchanged number of transmitted motion vectors and with only a modest increase in computational complexity. When implemented in an H.261 codec the new prediction method can improve the peak SNR 1–2 dB producing a significant visual improvement.     

H.264图像复杂度自适应的I帧码率控制算法

该文针对H.264帧内编码码率控制(RC)效果不佳的问题,提出了一种新颖的图像复杂度自适应I帧RC算法。首先用Sobel算子检测I帧亮度像素的梯度,建立44块的边缘方向直方图,得到每个44块最可能的帧内预测模式和相应重构块,最终获得与实际编码相近的残差图像。用残差的平均绝对值表达I帧编码复杂度,并提出了一种经验型码率-量化(R-Q)模型,同时考虑缓冲区状态和序列特性为I帧分配合适的目标比特,最后为每一个图像组(GOP)得到了合适的I帧量化参数(QP)。实验结果表明,该文算法能更准确地控制I帧输出码率,有效阻止缓冲区溢出和跳帧,得到更加平稳的视频质量,序列PSNR波动减少了60%以上。     

Iterative search strategy with selective bi-directional prediction for low complexity multiview video coding

The multiview video coding (MVC) extension of H.264/AVC is the emerging standard for compression of impressive 3D and free-viewpoint video. The coding structure in MVC adopts motion and disparity estimation to exploit temporal and inter-view dependencies in MVC. It results in a considerable increase in encoding complexity. Most of the computational burden comes from uni-directional and bi-directional prediction. In this paper, an iterative search strategy is designed to speed up the uni-directional prediction in MVC. It can work with an adaptive search range adjustment through a confidence measure of a loop constraint to obtain both motion and disparity vectors jointly. Furthermore, a selective bi-directional prediction algorithm is proposed to enhance the coding performance by analyzing the statistical characteristics of bi-directional prediction in MVC. Experimental results demonstrate that, by using the proposed fast search, the temporal and inter-view redundancies of multiview video can be eliminated sufficiently with low complexity.     

An efficient rate–distortion optimization method for dependent view in MV-HEVC based on inter-view dependency

Rate–distortion optimization (RDO) is utilized to select the optimal coding parameters in multi-view video coding (MVC), which employs a Lagrange multiplier to balance the relationship between the distortion and the bitrate. In this paper, an efficient RDO method for the dependent view (DV) in multi-view video (MVV) is proposed based on inter-view dependency. First of all, by investigating the sources of the distortion in the DV, a new distortion model for the DV is established. In addition, based on the proposed distortion model, an efficient Lagrangian multiplier decision for B frame is proposed by considering the inter-view dependency. Finally, the optimized Lagrangian multiplier for P frame is designed using the scaling factor which is deduced to have a linear relationship with the disparity between I frame and P frame. Experiment results demonstrate that compared with the original HTM-16.0 encoder, the proposed overall method reduces 12.19% BD-rate for the DV on average, bringing 0.40 dB BD-PSNR gain.     

On the methods and performances of rational downsizing video transcoding

Video transcoding is a popular technique for adapting the bit-rate or spatial/temporal resolution of a precoded video to suit better the constraints and requirements of different transmission networks and receiving devices. To minimize computational complexity, many fast methods have been proposed to obtain the motion vectors required for transcoding a precoded video through reducing its frame size by an integral factor. In this paper, we extend the existing work by developing and comparing several fast methods of downsizing precoded videos by a rational factor. Methods that outperform others under different conditions or with different computational requirements are identified, and an application scenario that can benefit from the proposed rational downsizing video transcoding is presented. An efficient scheme is also proposed to select the proper reduced frame size for sustaining the best possible video quality at a specified lower bit-rate. The superiority of the proposed transcoding approach in comparison with the existing integral downsizing video transcoding or cascaded video re-encoding methods is evident from the experimental results shown in this paper.     

Multi-resolution motion estimation and compensation based on adjacent prediction of frame difference in wavelet domain

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies,a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed.Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region.Then the motion region was extracted to carry out motion estimation and motion compensation on it.The experiment results show that the encoding efficiency of motion vector is promoted,the complexity of motion es timation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Reso lution Motion Estimation (MRME) is improved.     

Perceptual stereoscopic video coding using disparity just-noticeable-distortion model

In this paper, we propose perceptual stereoscopic video coding using a disparity just-noticeable-distortion (JND) model. We obtain the disparity JND model in stereo videos by disparity masking effects of the human visual system (HVS). The disparity JND model represents the maximum distortion of stereo perception that HVS cannot perceive. Based on the disparity JND model, we adjust prediction residuals to remove the perceptual redundancy of stereo videos. Thus, we achieve significant bit-rate saving while maintaining visual quality. Experimental results demonstrate that the proposed method significantly improves coding efficiency without loss of stereoscopic perceptual quality.     

Adaptive fractional motion and disparity estimation skipping in MV-HEVC

MV-HEVC can efficiently compress multiview video data captured from different viewpoints. To achieve high coding efficiency, it consists of not only inter coding but also interview coding. The inter coding includes a motion estimation (ME) process that reduces temporal redundancies between consecutive frames, and the interview coding performs a disparity estimation (DE) that reduces interview redundancies between neighboring views. As a result, MV-HEVC needs high encoding complexity to perform both ME and DE. In order to reduce the complexity, this paper proposes an adaptive fractional ME and DE skipping method in a partitioned inter prediction unit (PU) mode, based on a result of a 2 N × 2 N inter PU coding. Experimental results show that the proposed method efficiently reduces the encoding complexity with negligible coding loss, compared to conventional methods.     

Fast color correction for multi-view video by modeling spatio-temporal variation

In multi-view video, a number of cameras capture the same scene from different viewpoints. Color variations between the camera views may deteriorate the performance of multi-view video coding or virtual view rendering. In this paper, a fast color correction method for multi-view video is proposed by modeling spatio-temporal variation. In the proposed method, multi-view keyframes are defined to establish the spatio-temporal relationships for accurate and fast implementation. For keyframes, accurate color correction is performed based on spatial color discrepancy model that disparity estimation is used to find correspondence points between views, and linear regression is performed on these sets of points to find the optimal correction coefficients. For non-keyframes, fast color correction is performed based on temporal variations model that time-invariant regions are detected to reflect the change trends of correction coefficients. Experimental results show that compared with other methods, the proposed method can promote the correction speed greatly without noticeable quality degradation, and obtain higher coding performance.     

基于视差补偿预测的立体视频图像压缩编码

本文介绍了立体视频编码方法,并对其关键技术-视差补偿预测技术进行深入研究.本文所提出的基于视差分割的视差补偿预测算法是建立在可变尺寸块匹配算法的基础上,充分利用视差信息实现对目标图像帧的有效分割,并采用相适应的视差向量编码方案.与传统算法相比,在相同预测精度下,明显降低了视差信息编码开销.     

Adaptive Learning Based View Synthesis Prediction for Multi-View Video Coding

In the applications of Free View TV, pre-estimated depth information is available to synthesize the intermediate views as well as to assist multi-view video coding. Existing view synthesis prediction schemes generate virtual view picture only from interview pictures. However, there are many types of signal mismatches caused by depth errors, camera heterogeneity or illumination difference across views and these mismatches decrease the prediction capability of virtual view picture. In this paper, we propose an adaptive learning based view synthesis prediction algorithm to enhance the prediction capability of virtual view picture. This algorithm integrates least square prediction with backward warping to synthesize the virtual view picture, which not only utilizes the adjacent views information but also the temporal decoded information to adaptively learn the prediction coefficients. Experiments show that the proposed method reduces the bitrates by up to 18 % relative to the multi-view video coding standard, and about 11 % relative to the conventional view synthesis prediction method.     

Fast macroblock encoding algorithm based on rate-distortion activity for multiview video coding

Multiview video coding (MVC) is the appendix H of H.264/AVC, and it requires a great amount of time to compress multiple viewpoints׳ video with complex prediction structures. To reduce the whole computational complexity of MVC, this paper proposes a fast macroblock (MB) encoding algorithm based on rate-distortion (RD) activity, and it includes the fast mode decision and the fast motion/disparity estimation. First, the RD activity type of the current MB is calculated by utilizing the Skip/Direct RD cost and the average RD costs of classified MB modes. Then, through utilizing the RD activity type and RD costs of the estimated modes, the selection of candidate modes, the early decision of Skip/Direct mode, and the reduction of Inter8×8 mode estimation are all presented in the fast mode decision. By using the RD activity type and the correlations of vectors, the selection of search center and the prediction of search range are introduced in the fast motion/disparity estimation. In addition, the proposed algorithm can be applied to temporal and inter-view views as well as anchor and non-anchor frames. An experiment with a wide range of video scenes, camera setups and quantization parameters was implemented, and the results confirmed that the proposed algorithm can reduce the encoding time significantly while maintaining a similar RD performance as the original MVC encoder. Compared to the state-of-the-art algorithms, the proposed algorithm also demonstrated better performances in the various test cases.     

Adaptive video coding control for real-time H.264/AVC encoder

In this paper, we present a new adaptive video coding control for real-time H.264/AVC encoding system. The main techniques include: (1) the initial quantization parameter (QP) decision scheme is based on Laplacian of Gaussian (LoG) operators; (2) the MB-level QP calculation is based on the spatio-temporal correlation, in which the computation is less than the quadratic model used by H.264/AVC; (3) the adaptive GOP structure is proposed, in which the I-frame is adaptively replaced by an enhancement P-frame to improve the coding efficiency; (4) the scene change is detected with the complexity of adjacent inter-frames and the appropriate QP is re-calculated for the scene-change frame. The proposed algorithm is not only to save the computational complexity but also to improve coding quality. Compared to the JM12.4 reference under various sequences testing, the proposed algorithm can decrease coding time by 64.5% and improve PSNR by 1.52 dB while keeping the same bit-rate.     

Early merge mode decision for texture coding in 3D-HEVC

As the upcoming 3D video coding standard, high efficiency video coding (HEVC) based 3D video coding (3D-HEVC) has been drafted. In 3D-HEVC, the computational complexity of mode decision process is significantly high due to exhaustive modes’ checks for coding units (CU) derived from recursive quad-tree partitioning. In this paper, we propose an early merge mode decision method for complexity reduction of dependent texture views. First, inter-view correlation and hierarchical depth correlation of coding modes are separately analyzed for B frame and P frame. Then, conditions to early determine merge mode coded CUs are derived based on the correlations. All of the early determined CUs only check merge modes in the mode decision process, which brings considerable complexity reduction. Experimental results demonstrate that the proposed method can achieve average 20.4% of encoding time saving for dependent texture views with negligible rate distortion performance loss.