三维视频压缩研究进展

信息压缩是信息传输过程中的一个关键环节,随着三维显示和三维视频技术的发展和完善,未来的视频传输将不仅限于二维视频。但是,三维视频的数据量很大,这就给三维视频的传输带来了阻碍。因此,设计出高压缩比、高压缩效率的三维视频压缩技术,不但可以解决三维视频的传输问题,而且有利于促进三维视频及三维显示领域的进一步发展。本文系统地讨论了目前三维视频压缩技术的研究进展,在对各种技术特点研究的基础上,提出了进一步的研究和发展方向。     

实时视频压缩的计算结构

通过分析实时视频压缩算法的结构和数据结构，从并行策略和层次化结构的角度入手，系统地得出了实时视频压缩的计算结构模型。从芯片设计和应用的观点，对各种结构模型进行了性能比较，通过实例分析，证明了这些结构模型的有效性。     

浅谈视频压缩技术

在现代通信中,视频图像传输已成为重要内容之一。采用合适的视频图像压缩技术,减少传输数据量,是提高通信速度的重要手段。本文主要论述了视频压缩技术中常用的编码方法及H.26x、MPEG-x等视频压缩编码标准。     

实时视频压缩中块效应消除方法的研究

本文较全面的研究了目前存在的各种类型的块效应消除方法,提出了一种新型的用于消减视频编码中的块效应的双模式自适应滤波器（DMA）。同时,还提出了基于MSDS（the mean squared difference of slopese)的客观评估的量化指标,它较之PSNR更逼近块效应问题的本质,揭示了主观效果后面的数字实质.DMA通过分析块边界的像素行为,在两种完全独立的滤波模式间做出选择。它根据HVS（Human Visual System)特性,对平坦区域采用力度较强的平坦区域滤波器实现平滑滤波,而对细节丰富区域的块间像素,采用基于频谱分析的自适应滤波器既能有效消除块效应又能保留图像自身的高频信息,从而达到了十分理想的消除噪声的效果。此外,采用了优化策略使DMA的计算开销降到最低,可完全适应实时系统的需求。     

运动补偿技术及其在视频压缩编码中的应用

详细介绍了图像编码中运动补偿技术的原理及其在视频图像压缩处理中的应用,提出了采用混合编码实现视频图像处理中的运动补偿的方法,并讨论了这种方法的局限性。     

视频压缩流简化帧处理中若干问题研究

数据压缩技术主要用于减小视频数据的大小,以满足存储和传输的需要,但现有的图象处理技术必须先将视频压缩流完全解压后才能进行处理,本文讨论了不需要完全解压缩或仅需很小的解压就能直接对视流进行处理的方法,如ＭＰＥＧ压缩视频流中Ｐ帧和Ｂ帧以及常用的压缩域处理方法以及存在的问题,最后证明了在半象素运动矢量情况下ＭＰＥＧ简化帧抽取的准确性问题,视频压缩流在压缩域处理的特点是不仅减少了解压缩所需要的计算时间,而     

视频压缩编码技术的发展及应用

随着多媒体信息的数字化,视频数据量越来越大。在此基础上文章对视频压缩编码技术的产生背景、编码的基本原理以及压缩方法的分类进行了研究,并对国内外视频编码标准发展现状进行了分析,最后,预测了视频应用的未来发展趋势。     

基于Internet传输的视频压缩编码技术现状与发展

This paper provides an overview of the video compression coding techniques based on streaming video over the Internet from the viewpoint of video coding architecture especially. And the future research directions are pointed out at last.     

高清的秘密：高清视频压缩技术

就像练了缩骨功的武林高手可以毫发无损地通过狭窄的地道一样，经过处理后的大容量音视频信号也能通过有限的带宽传送，虽然不能保证毫发无损，但亮相在观众视线内的还是图像清晰，色彩亮丽，饱满圆润的高清晰视频影像，同时相比传统模拟信号、无雪花、鬼影、无色彩失真等问题存在——这就是高清视频压缩技术制造的高清秘密。[编者按]     

视频压缩编码的信号损伤

视频压缩的出现时随着二十世纪五十年代彩电的出现而进入人们视野,但是人们对图片、视频的压缩技术的大量研究却是从上世纪八十年代开始的.现在视频的传输大多采用数字电视传输,而数字电视传输的关键环节就是压缩编码系统对图像的压缩,系统性能的高低直接的决定了压缩后图片、视频的质量.本文从视频压缩编码的基本概念出发,较为详细的叙述了几种常见的视频压缩编码的信号损失类型,并对这几种信号损失情况提出了一些粗浅的解决办法.     

Spatiotemporal video representation and compression

In this paper is presented a novel approach for video representation and compression based on spectral compression of spatiotemporal cube. This solution is inspired by the spatiotemporal representation of video sequences.     

Motion estimation based color transfer and its application to color video compression

In this paper a novel scheme for color video compression using color transfer technique is proposed. Towards this, a new color transfer mechanism for video using motion estimation is presented. Encoder and decoder architectures for the proposed compression scheme are also presented. In this scheme, compression is achieved by firstly discarding chrominance information for all but selected reference frames and then using motion prediction and discrete cosine transform (DCT) based quantization. At decompression stage, the luminance-only frames are colored using chrominance information from the reference frames applying the proposed color transfer technique. To integrate color transfer mechanism with hybrid compression scheme a new color transfer protocol is defined. Both compression scheme and color transfer work in YCbCr color space.

面向视频传感器网络的视频压缩方法设计

视频传感器网络在监控过程中会产生大量数据,为此提出一种改进的基于对象的视频压缩方法.首先,运用改进的混合高斯模型进行背景建模;其次,提出宏块分类方法,对视频帧图像进行宏块分类;然后,利用宏块分类结果,实现前景和背景的分离;最后,分别对前景和背景进行压缩,形成各自的编码流.实验结果表明,该方法具有比MPEG-4更强的压缩能力,满足视频传感器网络的视频压缩需求.     

Efficient compression and network adaptive video coding for distributed video surveillance

The availability of cheap network based video cameras and the prevalence of wireless networks has lead to a major thrust towards deployment of large scale Distributed Video Surveillance (DVS) systems. This has opened up an important area of research to deal with the issues involved in DVS system for efficient collection and transmission of large scale video streams from the cameras at the guarded sites, to the end users in possibly constrained network conditions. In this paper, we propose a framework based on content-based video classification and scalable compression scheme to provide a robust bandwidth efficient video transmission for DVS. The scheme builds on a Discrete Wavelet Transform (DWT) based Color-Set Partitioning for Hierarchical Trees (CSPIHT) coding to obtain a scalable bitstream. Wavelet domain segmentation and compression assists in development of a DVS architecture. The architecture includes a novel module for dynamic allocation of Network bandwidth based on the current available resources and constraints. Different frame constituents are optimally coded based on their relative significance, perceptual quality, and available estimate of network bandwidth. Experimental result over different video sequences and simulations for Network conditions demonstrate the efficient performance of the approach.     

Adding lossless video compression to MPEGs

In this correspondence, we propose to add a lossless compression functionality into existing MPEGs by developing a new context tree to drive arithmetic coding for lossless video compression. In comparison with the existing work on context tree design, the proposed algorithm features in 1) prefix sequence matching to locate the statistics model at the internal node nearest to the stopping point, where successful match of context sequence is broken; 2) traversing the context tree along a fixed order of context structure with a maximum number of four motion compensated errors; and 3) context thresholding to quantize the higher end of error values into a single statistics cluster. As a result,the proposed algorithm is able to achieve competitive processing speed, low computational complexity and high compression performances, which bridges the gap between universal statistics modeling and practical compression techniques. Extensive experiments show that the proposed algorithm outperforms JPEG-LS by up to 24% and CALIC by up to 22%, yet the processing time ranges from less than 2 seconds per frame to 6 seconds per frame on a typical PC computing platform.     

Arbitrarily shaped virtual-object based video compression

Object based compression techniques are widely believed to have the potential to give the best compression results for a given signal quality. However, true object tracking and extraction are difficult and computationally expensive. In this paper, an arbitrarily shaped virtual-object compression method is developed. The method is similar to the object based compression methods in that it separates the changing portion of the video from the stationary portion, and encodes them independently. The changing portion of the video is grouped as a 3D arbitrarily shaped virtual-object whereas the unchanged portion of the video is grouped as background. The arbitrarily shaped virtual object is coded using 3D wavelet compression whereas stationary background is coded as a single frame using 2D wavelet compression. Experimental results demonstrate that the newly developed method has comparable performance with the state-of-the-art compression methods and significantly outperforms rectangular virtual-object compression.     

基于矢量量化的数字视频压缩技术

对基于矢量量化的数字视频压缩技术进行了论述，并根据分析结果提出了一种新的矢量量化算法——多级矢量量化联合编码算法，该算法保持了多级矢量量化算法编码速度快、图像相关性小等特点，同时提高了编码质量。实验表明，该算法与已有的算法相比具有较高的图像质量和更高的压缩率。     

Volumetric video compression for interactive playback

We develop a volumetric video system which supports interactive browsing of compressed time-varying volumetric features (significant isosurfaces and interval volumes). Since the size of even one volumetric frame in a time-varying 3D data set is very large, transmission and on-line reconstruction are the main bottlenecks for interactive remote visualization of time-varying volume and surface data. We describe a compression scheme for encoding time-varying volumetric features in a unified way, which allows for on-line reconstruction and rendering. To increase the run-time decompression speed and compression ratio, we decompose the volume into small blocks and encode only the significant blocks that contribute to the isosurfaces and interval volumes. The results show that our compression scheme achieves high compression ratio with fast reconstruction, which is effective for interactive client-side rendering of time-varying volumetric features.     

基于内容的视频压缩改进算法

由于时间的连续性,视频前后帧图像有很大的相似性,视频图像前后帧存在着很大的时间冗余.针对视频图像的帧间冗余,在传统的视频编码算法基础上,提出一种基于匹配内容的视频压缩改进算法,根据实际视频图像的不同,选取不同的编码策略,并采用零树小波变换算法,使压缩比和实时性得到很大的提高.     

Traffic and video quality with adaptive neural compression

Video sequences are major sources of traffic for broadband ISDN networks, and video compression is fundamental to the efficient use of such networks. We present a novel neural method to achieve real-time adaptive compression of video. This tends to maintain a target quality of the decompressed image specified by the user. The method uses a set of compression/decompression neural networks of different levels of compression, as well as a simple motion-detection procedure. We describe the method and present experimental data concerning its performance and traffic characteristics with real video sequences. The impact of this compression method on ATM-cell traffic is also investigated and measurement data are provided.