Highly scalable video compression with scalable motion coding

A scalable video coder cannot be equally efficient over a wide range of bit rates unless both the video data and the motion information are scalable. We propose a wavelet-based, highly scalable video compression scheme with rate-scalable motion coding. The proposed method involves the construction of quality layers for the coded sample data and a separate set of quality layers for the coded motion parameters. When the motion layers are truncated, the decoder receives a quantized version of the motion parameters used to code the sample data. The effect of motion parameter quantization on the reconstructed video distortion is described by a linear model. The optimal tradeoff between the motion and subband bit rates is determined after compression. We propose two methods to determine the optimal tradeoff, one of which explicitly utilizes the linear model. This method performs comparably to a brute force search method, reinforcing the validity of the linear model itself. Experimental results indicate that the cost of scalability is small. In addition, considerable performance improvements are observed at low bit rates, relative to lossless coding of the motion information.     

Error-resilient image and video coding for wireless communicationsystems

Current techniques for coding images and video sources with resilience to channel errors can remove much of the need for complex high-redundancy channel coding and provide a graceful degradation of performance with decreasing channel quality. The main function of these error-resilient techniques is to reduce the propagation of errors within the decoded data. Two main techniques are discussed in detail: the error-resilient entropy code (EREC) and pyramid vector quantisation (PVQ). The paper concludes with a comparison of the relative merits of these systems and areas for further consideration     

Drift-resistant SNR scalable video coding.

We address the problem of enhancement layer drift estimation for fine granular scalable video. An optimal per-pixel drift estimation algorithm is introduced. The encoder assumes that there is some truncation of the enhancement layer, which does not allow the enhancement layer reference to be properly reconstructed, and the encoder recursively estimates the associated drift and chooses coding modes accordingly. The approach yields performance gains of about 1 dB across low to medium rates. In addition, we investigate dual frame prediction, for both base and enhancement layer, with pulsed-quality allocation in the base     

基于TSSA软件架构的视频压缩编码系统

针对数字监控系统的需求提出了一种基于多媒体DSP PNXl300 TSSA架构的适用的MPEG-4视频编码方案，介绍了TSSA的概念，TSSA中AL和OL层的关系以及如何使用TSSA来搭建视频压缩编码系统。     

基于H.26L的精细度可伸缩视频编码

提出了一种基于H．26L精细度可伸缩(fine granularity scalability)视频编码方案，称为EFGS-H．26L。在该方案中，以MPEG-4的FGS为基础构造了一种新的可伸缩结构(EFGS，enhanced fine granularity scalability)，在EFGS结构中，基本层采用H．26L编码，增强层采用类似于JPEG2000的基于上下文的位平面编码。由于H．26L优良的编码性能，使得基本层的编码效率大大提高，为了提高增强层的编码效率，首先把残余图像按子带的顺序重新排列，这样就可以利用子带系数的相关性来实现冗余信息消除。JPEG2000标准中的EBCOT算法已经被证明是非常高效的位平面编码方法，所以对重排后的DCT系数采用一种类似于JPEG2000的基于上下文的位平面编码方法。实验结果证明，在高比特率时，本文提出的精细度可伸缩编码方案编码效率比MPEG-4中的FGS提高3．0dB左右。     

分布式压缩视频编码的帧分类重构方法研究

在很多的应用场景中需要具有低复杂度的视频编码器,新兴的分布式视频编码和压缩感知技术正好适用于这些场景中,因而出现了一种新的视频编码方案——分布式压缩视频编码。在现有的一些分布式压缩视频编码方案中,视频帧在编码端是独立编码,在解码端进行联合解码,具体来说就是关键帧独立解码,非关键帧在由关键帧生成的边信息的帮助下进行解码,这就忽略了非关键帧之间的相关性。本文提出一个新的分布式视频编码方案,将非关键帧分为主非关键帧和次非关键帧,主非关键帧利用关键帧生成地边信息进行解码,而次非关键帧先利用相邻的主非关键帧进行观测值预测,然后再利用关键帧生成的边信息进行解码。实验结果表明,在本文提出的框架下,非关键帧的重构质量提高了有2dB~4dB。      

Perceptual-based distributed video coding

In this paper, we propose a perceptual-based distributed video coding (DVC) technique. Unlike traditional video codecs, DVC applies video prediction process at the decoder side using previously received frames. The predicted video frames (i.e., side information) contain prediction errors. The encoder then transmits error-correcting parity bits to the decoder to reconstruct the video frames from side information. However, channel codes based on i.i.d. noise models are not always efficient in correcting video prediction errors. In addition, some of the prediction errors do not cause perceptible visual distortions. From perceptual coding point of view, there is no need to correct such errors. This paper proposes a scheme for the decoder to perform perceptual quality analysis on the predicted side information. The decoder only requests parity bits to correct visually sensitive errors. More importantly, with the proposed technique, key frames can be encoded at higher rates while still maintaining consistent visual quality across the video sequence. As a result, even the objective PSNR measure of the decoded video sequence will increase too. Experimental results show that the proposed technique improves the R-D performance of a transform domain DVC codec both subjectively and objectively. Comparisons with a well-known DVC codec show that the proposed perceptual-based DVC coding scheme is very promising for distributed video coding framework.     

Multidimensional quantizers for scalable video compression

Scalable video compression requires the creation of an encoded bit stream that may be decoded in part if channel bandwidth drops, decoder resources are limited, or a smaller image than the source is desired. A separable spatiotemporal subband decomposition is combined with vector and lattice quantizers modified so that the individual subbands may be decoded scalably. This results in finer bandwidth control and more flexibility than simply discarding entire subbands     

Absolute value coding for robust and scalable video coding

Absolute value coding is introduced as a method for significantly reducing temporal drift within a motion compensated predictive video codec in the presence of loss. Drift reduction both improves error resilience and enables scalability by omission of parts of the bit-stream. In conjunction with matching pursuits, the system can be used to provide a displaced frame difference codec using fixed length codewords, which further improves error resilience and facilitates simple bit-stream editing.     

A fully scalable motion model for scalable video coding.

Motion information scalability is an important requirement for a fully scalable video codec, especially for decoding scenarios of low bit rate or small image size. So far, several scalable coding techniques on motion information have been proposed, including progressive motion vector precision coding and motion vector field layered coding. However, it is still vague on the required functionalities of motion scalability and how it collaborates flawlessly with other scalabilities, such as spatial, temporal, and quality, in a scalable video codec. In this paper, we first define the functionalities required for motion scalability. Based on these requirements, a fully scalable motion model is proposed along with tailored encoding techniques to minimize the coding overhead of scalability. Moreover, the associated rate distortion optimized motion estimation algorithm will be provided to achieve better efficiency throughout various decoding scenarios. Simulation results will be presented to verify the superiorities of proposed scalable motion model over nonscalable ones.     

Error concealment for SNR scalable video coding

This paper proposes an efficient error concealment method for SNR scalable coded video. The algorithm adaptively selects a proper concealment candidate from the base or the enhanced pictures to conceal the artifact of a lost enhancement block. To determine the best concealment candidate, we propose a trial process in which the concealment candidates are examined based on two criteria: (1) picture continuity at the border of concealed macroblocks, and (2) to satisfy the coding distortion bound of the base layer coefficients when they are available. For the latter, requantization of the concealed picture with the base layer quantizer step size and its dequantized pixels should result in zero distortion. We have implemented the method on a proposed SNR scalable H.264 video codec and compared the decoded video quality against just copying the base layer pixels into the enhanced picture. Simulation results show that the proposed method can achieve a considerable improvement by up to 3 dB especially in situations where the enhancement layer contains a large portion of the picture information. This will make scalable video transmission more successful over unreliable channels.     

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.     

Low complexity distributed video coding

ContextConventional video encoding is a computationally intensive process that requires a lot of computing resources, power and memory. Such codecs cannot be deployed in remote sensors that are constrained in terms of power, memory and computational capabilities. For such applications, distributed video coding might hold the answer.ObjectiveIn this paper, we propose a distributed video coding (DVC) architecture that adheres to the principles of DVC by shifting the computational complexity from the encoder to the decoder and caters to low-motion scenarios like video conferencing and surveillance of hallways and buildings.MethodThe architecture presented is block-based and introduces a simple yet effective classification scheme that aims at maximizing the use of skip blocks to exploit temporal correlation between consecutive frames. In addition to the skip blocks, a dynamic GOP size control algorithm is proposed that instantaneously alters the GOP size in response to the video statistics without causing any latency and without the need to buffer additional frames at the encoder. To facilitate real-time video delivery and consumption, iterative channel codes like low density parity check codes and turbo codes are not used and in their place a Bose–Chaudhuri–Hocquenghem (BCH) code with encoder rate control is used.ResultsIn spite of reducing the complexity and eliminating the feedback channel, the proposed architecture can match and even surpass the performance of current DVC systems making it a viable solution as a codec for low-motion scenarios.ConclusionWe conclude that the proposed architecture is a suitable solution for applications that require real-time, low bit rate video transmission but have constrained resources and cannot support the complex conventional video encoding solutions.Practical implicationsThe practical implications of the proposed DVC architecture include deployment in remote video sensors like hallway and building surveillance, video conferencing, video sensors that are deployed in remote regions (wildlife surveillance applications), and capsule endoscopy.     

Error-resilient SPIHT image coding

The authors develop an efficient error-resilient scheme for the set partitioning in hierarchical trees (SPIHT) technique, one of the most successful image compression algorithms. By partitioning the coded data sequence and adding appropriate side information, the proposed algorithm provides significantly better PSNR performance over noisy channels with a minimal increase in the coding complexity     

Spatially scalable video compression employing resolution pyramids

A spatially scalable video coding scheme for low bit rates is proposed. The codec is especially well suited for communications applications because it is based on motion-compensated predictive coding which provides the necessary low-delay property. The frames to be coded are decomposed into a Gaussian pyramid. Motion estimation and compensation are performed between corresponding pyramid levels of successive frames. We show that, to fulfill specific needs of spatial scalability, the motion compensation on each level must result in compatible prediction errors (displaced frame differences, DFD). Compatibility of the prediction errors means that the pyramid formed by independently obtained DFD's (the DFD pyramid) is close to a Gaussian pyramid decomposition of the DFD of the highest resolution level. From the DFD pyramid, a least squares Laplacian pyramid is derived, which is quantized and coded. The DFD encoder outputs an embedded bit stream. Thus, the coder control may truncate the bit stream at any point, and can keep a fixed rate. The motion vector fields obtained at the different resolution levels are also encoded by employing a pyramid approach. Simulation results show that the proposed coder achieves a coding gain compared to simulcast coding     

Error-resilient coding of H.264 based on periodic macroblock

For the compressed video, since an inter-frame depends on the previously encoded frame, the error in one inter-frame may propagate to the following inter-frames. In this paper, we present a new error-resilient coding scheme to alleviate the effect of error propagation for the new coding standard H.264. In this new coding standard, multiple reference frame is adopted to improve the coding efficiency. By making use of the reference frame buffer in the encoder, we can reference some macroblocks in every n/sup th/ inter-frame to the frame that is n frames interval away, and these macroblocks are named as periodic macroblocks. The periodic macroblock can efficiently alleviate the error propagation between two frames that contain periodic macroblocks. We prove it in theory that encoding selected periodic macroblocks will reduce the loss probability of pixel. The selection of periodic macroblock is based on the distortion expectation of each macroblock in every n/sup th/ frame. The number of periodic macroblocks in every n/sup th/ frame can be adjusted according to the available transmission bandwidth, as the periodic macroblock will consume little more bits. The simulation results prove that the periodic macroblocks can obviously improve the quality of video at different macroblock loss rates. When the macroblock lost rate is 15% in every frame, the PSNR of video sequence can be improved about 3dB with 5% bitrate increase.     

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。     

Model design for scalable two-dimensional model-based video coding

Scalable and very low bit rate video coding is vital for audio-visual conversational services over narrow bandwidth channels. A novel model design scheme is proposed in order to make the points of an object model represent the motion more accurately, which will in turn enable better compression. Experimental results demonstrate the performance of the proposed scheme.