适合于渐进传输的嵌入式三维小波视频构架

描述了怎样有效地将基本层视频编码H.264嵌入到3D小波视频编码的构架,在3D可扩展视频编码方案中提取出基本视频层可以获得诸如闭环短时预测、环路滤波和率失真最优化等特点,还能与现有的视频标准相适应,相对于3D小波视频编码可改善在低码率条件下的信噪比.     

一种时域质量稳定的三维小波视频编码率控制技术

三维小波视频编码提供了分辨率、时域和质量的可伸缩性。在三维小波编码中，如何调整各小波频带间的码率分配以达到最佳的码率控制至关重要。就小波变换和反变换的结构而言，常规的三维小波视频编码方法会导致解码视频帧沿时间方向播放质量的周期振荡，这种周期的振荡会影响了观看质量。本文研究了重建信号与小波频带间失真分布的关系，提出了一种具有稳定的时域解码质量的率控制方法，实验结果表明该算法在保证播放质量稳定的同时，还具有与常规三维小波视频编码方法近似的平均解码质量。     

Lifting-based invertible motion adaptive transform (LIMAT) framework for highly scalable video compression

We propose a new framework for highly scalable video compression, using a lifting-based invertible motion adaptive transform (LIMAT). We use motion-compensated lifting steps to implement the temporal wavelet transform, which preserves invertibility, regardless of the motion model. By contrast, the invertibility requirement has restricted previous approaches to either block-based or global motion compensation. We show that the proposed framework effectively applies the temporal wavelet transform along a set of motion trajectories. An implementation demonstrates high coding gain from a finely embedded, scalable compressed bit-stream. Results also demonstrate the effectiveness of temporal wavelet kernels other than the simple Haar, and the benefits of complex motion modeling, using a deformable triangular mesh. These advances are either incompatible or difficult to achieve with previously proposed strategies for scalable video compression. Video sequences reconstructed at reduced frame-rates, from subsets of the compressed bit-stream, demonstrate the visually pleasing properties expected from low-pass filtering along the motion trajectories. The paper also describes a compact representation for the motion parameters, having motion overhead comparable to that of motion-compensated predictive coders. Our experimental results compare favorably to others reported in the literature, however, our principal objective is to motivate a new framework for highly scalable video compression.     

提升方案小波和位平面下的图像质量可分级编码研究

提出了一种基于位平面的图像质量可分级编码方法,结合小波变换的良好空间-频率等特性,对静止图像进行位平面编码和算术编码,并在解码时根据给定解码的数率不同对位平面进行重构以实现图像的质量可分级性。实验结果证明,该方法实现简单,编解码速度快,在保证具有很好的编码效果的前提下,可以实现图像的质量可分级编码。     

可伸缩性视频编码的码率分配算法

本文研究了渐进的精细的可伸缩性(Progressive Fine Granular Scalable,PFGS)视频编码的增强层码流的码率分配问题,它是由PFGS各帧的增强层码流长度不同引起的.我们首先建立了PFGS增强层的多帧联合的率失真(rate-distortion,R-D)函数,并通过MPEG-4标准测试序列检验了它的正确性.然后利用联合率失真函数给出了局部最优的码率分配算法,并进行了简化使得它的复杂性极低,非常适合流化视频(streaming video)服务器使用.实验结果显示本文提出的算法不仅使得各帧图像的解码质量比较平衡,而且将PFGS的编码效率提高了将近0.5dB.     

基于帧间去相关的超光谱图像压缩方法

针对超光谱图像的特点和硬件实现的实际需要,提出了一种基于小波变换的前向预测帧间去相关超光谱图像压缩算法。通过图像匹配和帧间去相关,消除超光谱图像帧间的冗余,对残差图像的压缩采用基于小波变换的快速位平面结合自适应算术编码的压缩算法,按照率失真准则控制输出码流,实现了对超光谱图像的高保真压缩。通过实验证明了该方案的有效性,基于小波变换的快速位平面结合自适应算术编码的压缩算法速度优于SPIHT,而且易于硬件实现。     

基于分段式拟合的低比特率图像压缩编码方法

为了提高图像在低比特率条件下的解码质量和视觉效果,该文提出一种基于稀疏分解的低比特率图像压缩编码新方法。利用二维不可分离、具有各向异性尺度的墨西哥草帽小波作为生成函数,这种函数构建的冗余字典能够有效捕获图像边缘轮廓特征。为降低原子投影系数的冗余度和减小其编码量,对图像稀疏分解投影的系数采用分段式拟合。获得的图像压缩码流具有渐进特性的,满足现代无线通信对可伸缩码流的要求。实验结果表明,在低比特率下,该文方法与JPEG2000方法和通常的稀疏分解编码法相比,有更高的峰值信噪比;解压图像无振铃效应,主观效果好。     

Interlayer bit allocation for scalable video coding

In this paper, we present a theoretical analysis of the distortion in multilayer coding structures. Specifically, we analyze the prediction structure used to achieve temporal, spatial, and quality scalability of scalable video coding (SVC) and show that the average peak signal-to-noise ratio (PSNR) of SVC is a weighted combination of the bit rates assigned to all the streams. Our analysis utilizes the end user's preference for certain resolutions. We also propose a rate-distortion (R-D) optimization algorithm and compare its performance with that of a state-of-the-art scalable bit allocation algorithm. The reported experiment results demonstrate that the R-D algorithm significantly outperforms the compared approach in terms of the average PSNR.     

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.     

Motion information scalability for MC-EZBC

Interframe wavelet video coding algorithm has received much attention lately because of its high coding efficiency and flexible temporal and spatial scalability. It combines the motion-compensated temporal filtering technique together with the wavelet embedded zeroblock coding technique. Blending these two techniques in a nice manner enables it achieving three types of scalability: SNR, temporal and spatial, in one single bit-stream. However, the performance of the interframe wavelet video coding at low bit-rates is less satisfactory because the bit-rate of the non-scalable motion information is too high.In this paper, we extend the framework of Motion Compensated Embedded Zero Block Coding (MC-EZBC) proposed by RPI (Improved MC-EZBC with Quarter-pixel Motion Vectors, ISO/IEC/JTC1 SC29/WG11 doc. No. m8366, Fairfax, May 2002). Our major contribution is splitting the motion information in MC-EZBC into a few layers. At very low bit-rates only the “coarse” motion vectors are transmitted. Therefore, we are able to produce compressed bit streams at a lower bit-rate and the associated picture quality is significantly better than that of the original scheme. The overhead due to motion information partitioning is negligible at higher rates. Hence, the rate-distortion performance at high rates is about the same as that of the original scheme. In addition, a Hilbert curve scan order is proposed to increase the efficiency up to 5% in encoding the differential motion vectors.     

A joint source-channel distortion model for JPEG compressed images.

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.     

A rate-distortion analysis on motion prediction efficiency and mode decision for scalable wavelet video coding

A rate-distortion model for describing the motion prediction efficiency in interframe wavelet video coding is proposed in this paper. Different from the non-scalable video coding, the scalable wavelet video coding needs to operate under multiple bitrate conditions and it has an open-loop structure. The conventional Lagrangian multiplier, which is widely used to solve the rate-distortion optimization problems in video coding, does not fit well into the scalable wavelet structure. In order to find the rate-distortion trade-off due to different bits allocated to motion and textual information, we suggest a motion information gain (MIG) metric to measure the motion prediction efficiency. Based on this metric, a new cost function for mode decision is proposed. Compared with the conventional Lagrangian method, our experiments show that the proposed method is less extraction-bitrate dependent and generally improves both the PSNR performance and the visual quality for the scalability cases.     

Robust Video Transmission With Distributed Source Coded Auxiliary Channel

We propose a novel solution to the problem of robust, low-latency video transmission over lossy channels. Predictive video codecs, such as MPEG and H.26x, are very susceptible to prediction mismatch between encoder and decoder or “drift” when there are packet losses. These mismatches lead to a significant degradation in the decoded quality. To address this problem, we propose an auxiliary codec system that sends additional information alongside an MPEG or H.26x compressed video stream to correct for errors in decoded frames and mitigate drift. The proposed system is based on the principles of distributed source coding and uses the (possibly erroneous) MPEG/H.26x decoder reconstruction as side information at the auxiliary decoder. The distributed source coding framework depends upon knowing the statistical dependency (or correlation) between the source and the side information. We propose a recursive algorithm to analytically track the correlation between the original source frame and the erroneous MPEG/H.26x decoded frame. Finally, we propose a rate-distortion optimization scheme to allocate the rate used by the auxiliary encoder among the encoding blocks within a video frame. We implement the proposed system and present extensive simulation results that demonstrate significant gains in performance both visually and objectively (on the order of 2 dB in PSNR over forward error correction based solutions and 1.5 dB in PSNR over intrarefresh based solutions for typical scenarios) under tight latency constraints.      

基于多视点视频编码的差错控制算法

 多视点视频编码(Multiview Video Coding,MVC)利用运动估计和视差估计取得了较好的编码性能,但在易错的网络环境下传输MVC视频码流,将导致差错在视点内与视点间进行扩散.针对多视点视频的编码特性,提出了一种端到端的失真度估计模型,并将此模型与率失真优化相结合得到一种基于联合信源信道的编码模式选择算法.实验结果表明该方法能够在易错网络环境下有效的提高多视点视频的传输效率.     

Motion and texture rate-allocation for prediction-based scalable motion-vector coding

Modern video coding applications require data transmission over variable-bandwidth wired and wireless network channels to a variety of terminals, possibly having different screen resolutions and available computing power. Scalable video coding technology is needed to optimally support these applications. Recently proposed wavelet-based video codecs employing spatial-domain motion-compensated temporal filtering (SDMCTF) provide quality, resolution and frame-rate scalability while delivering compression performance comparable to that of H.264, the state-of-the-art in single-layer video coding. These codecs require quality-scalable coding of the motion vectors to support a large range of bit-rates with optimal compression efficiency. In this paper, the practical use of prediction-based scalable motion-vector coding in the context of scalable SDMCTF-based video coding is investigated. Extensive experimental results demonstrate that, irrespective of the employed motion model, our prediction-based scalable motion-vector codec (MVC) systematically outperforms state-of-the-art wavelet-based solutions for both lossy and lossless compression. A new rate-distortion optimized rate-allocation strategy is proposed, capable of optimally distributing the available bit-budget between the different frames and between the texture and motion information, making the integration of the scalable MVC into a scalable video codec possible. This rate-allocation scheme systematically outperforms heuristic approaches previously employed in the literature. Experiments confirm that by using a scalable MVC, lower bit-rates can be attained without sacrificing motion-estimation efficiency and that the overall coding performance at low rates is significantly improved by a better distribution of the available rate between texture and motion information. The only downside of scalable motion-vector coding is a slight performance loss incurred at high bit-rates.     

无反馈分布式视频编码中的速率控制算法

针对现有比特平面级编码端速率控制算法估计精度要求高的问题,提出了一种帧级编码端速率控制算法。该算法通过在编码端利用分层快速运动补偿内插产生高质量的边信息估计,并根据循环移位去除比特平面间的级别性,使每个比特平面的编码速率均匀化,从而实现帧级别的速率控制。实验结果表明,与现有算法相比,所提算法对中高速运动视频边信息估计质量有明显提升,且解码视频的平均PSNR(peak signal-to-noise ratio)均有提高。     

Unconstrained motion compensated temporal filtering (UMCTF) for efficient and flexible interframe wavelet video coding

We introduce an efficient and flexible framework for temporal filtering in wavelet-based scalable video codecs called unconstrained motion compensated temporal filtering (UMCTF). UMCTF allows for the use of different filters and temporal decomposition structures through a set of controlling parameters that may be easily modified during the coding process, at different granularities and levels. The proposed framework enables the adaptation of the coding process to the video content, network and end-device characteristics, allows for enhanced scalability, content-adaptivity and reduced delay, while improving the coding efficiency as compared to state-of-the-art motion-compensated wavelet video coders. Additionally, a mechanism for the control of the distortion variation in video coding based on UMCTF employing only the predict step is proposed. The control mechanism is formulated by expressing the distortion in an arbitrary decoded frame, at any temporal level in the pyramid, as a function of the distortions in the reference frames at the same temporal level. All the different scenarios proposed in the paper are experimentally validated through a coding scheme that incorporates advanced features (such as rate-distortion optimized variable block-size multihypothesis prediction and overlapped block motion compensation). Experiments are carried out to determine the relative efficiency of different UMCTF instantiations, as well as to compare against the current state-of-the-art in video coding.     

基于帧内区域的细粒度可扩展视频编码最优码率分配算法

MPEG-4 FGS是MPEG-4中精细可扩展性编码方法,由于采用帧8*8交织的位平面编码结构,无法支持帧内区域级的动态码率分配,不适合基于内容的增强和流化传输,针对MPEG-4 FGS这编码限制,本文根据MPEG-7的内容描述标准,提出了一种基于帧内区域的细粒度可扩展A-FGS编码,实现了实时的帧内区域流化编码,并就该编码提出了一种最优码率分配算法.利用帧内区域8*8宏块高位平面非零系数很少的特点,提出了动态码率分配算法,使在中等码率范围内编码效率提高了0.5dB左右.     

Convex Optimization-Based Bit Allocation for Video Coding

This paper presents a new convex optimization-based bit allocation framework for video coding. Motivated by the statistical analysis of the relationship between the rate and the corresponding distortion in typical video sequences, an improved empirical rate-distortion model with more flexibility in explaining the experimental observations is proposed. The convexity and monotonicity properties of the proposed model allow us to formulate the bit allocation problem as a convex programming problem, which can be solved using interior-point methods. Coupled with the region of interest (ROI) functionality and the technique of MB classification, the proposed bit allocation scheme is then applied to the problem of frame-level bit allocation for various video coding standards employing motion compensated hybrid DCT/DPCM technique. Similar bit allocation scheme is also developed for MPEG-4 video object coding at the object level. The relevant model parameters are determined using previously encoded data by means of linear regression. Simulation results show that the proposed algorithms can achieve considerably better PSNR performance than the conventional approaches for the tested video sequences, at the expenses of slight increase in coding complexity.