Scalable coding is one of the important methods to resolve these problems.
可分级编码是解决这些问题的重要方法之一。
Scalable coding and shape coding are two pivotal techniques in MPEG-4 video coding.
可扩展编码和形状编码技术是MPEG - 4视频编码部分的两个关键技术。
Speech scalable coding is widely considered to be a good scheme for multimedia communication under different conditions.
为了保证在不同通信条件下语音通信的正常进行，采用可伸缩编码技术是目前得到广泛认可的方案。
The video scalable coding technique, one of core technology in media streaming, have been thought as the important study field.
作为流媒体的核心技术之一，视频的可分级编码技术已经成为一个重要的研究领域。
Finally, pointed out the deficiency of the scheme and what question needs further study, and forecast bandwidth scalable coding.
最后，指出该设计方案的不足之处及需要进一步研究的问题，并展望带宽可伸缩编码的前景。
In this paper, we present a novel structure for spatially scalable video coding, that is, fine-granularity spatially scalable coding.
提出了一种新颖的空间可伸缩视频编码方案-精细粒度空间可伸缩编码。
And this paper mainly researches on scalable coding, especially Fine Granular Scalability (FGS) coding, and the problems of its transmission.
本论文主要研究了可分级编码，特别是面向网络的精细可扩展编码，以其在网络上的相关传输问题。
This paper has introduced the scalable coding of MPEG-4, and focuses on the space scalable coding which is discussed and studied by many people.
本文主要介绍了MPEG - 4的分层编码，重点放在目前大家讨论和研究比较多一些的空域分层编码上。
This paper presents a new Fine Granular Scalable coding based on the image object, which incorporate the image object coding with the Bit plane coding.
为此提出了一种基于对象的精细可伸缩性编码方法，该方法将对象编码与位平面编码相结合。
Scalable coding method for contoure feature data is researched. A scalable coding method of contoure features is presented based on progressive coding of TIN.
对等高线的可伸缩性编码进行了研究，提出了一种基于三角网渐进编码的等高线数据的可伸缩性编码方法。
In the speech expandable code aspect, at present already proposed the many kinds of scalable coding plans, also have the corresponding international standards.
在语音可伸缩编码方面，目前已经提出了多种可伸缩编码的方案，国际上也制定了相应的标准。
This article analyzes several problems existing in multimedia transmission in WMN and introduces the application of adaptive transmission based on scalable coding.
文中分析了WMN传输多媒体业务所存在的问题，并且介绍了基于分级编码的自适应传输在该网络中的应用。
Scalable video coding(SVC) technology is a new domain in the processing of image and video, and there are many results of SVC at present.
可伸缩性视频编码（SVC）技术是图像和视频处理中一个新的研究领域，近年来取得了很多成果。
Scalable video coding based on MCTF (motion compensated temporal filtering) has been thought of as the important study field for it's validity of removing temporal correlation.
基于运动补偿时间滤波的可伸缩视频编码因其能有效去除时间相关性，而成为视频标准组织目前研究的热点。
This paper makes a deep insight into two problems of object-based fine granular scalable video coding in the wavelet domain, namely video object coding and motion estimation techniques.
本文对基于对象的小波域视频细粒度可分级编码中的两个关键问题，即视频对象编码和运动估计技术进行了深入研究。
In this paper, a new intra prediction algorithm for enhancement layer in spatially scalable video coding is proposed.
针对空间可扩展视频编码，提出了一种新的增强层上的帧内预测算法。
Study of Scalable Video Coding Based on Lifting Wavelet Motion Compensation Technology;
现有的比较成熟的可伸缩编码框架是基于运动补偿时域滤波技术的。
The paper proposed a new spatial scalable shape coding algorithm for MPEG-4 based on the features of video's shape information.
文章在分析视频图像二值形状信息特点的基础上，提出了一种新的MPEG - 4二值形状空域可扩展编码算法。
In response to this mandate, scalable video coding technology came into being.
针对这一任务的变化，可伸缩视频编码技术应运而生。
The redundancy is about 10 to 20 percents. An ROI-first transmission method of scalable video coding is proposed.
提出了一种感兴趣区域优先传输的可伸缩视频编码传输方法。
The initialization tables have statistics of a significant coefficient pass for a previous encoded frame or slice using scalable video coding.
所述初始化表具有使用可缩放视频编码的先前经编码帧或片段的有效系数进程的统计数据。
We address the scalable video bitstream protection and adaptation problem by a set of joint source network coding techniques for robust streaming video to heterogeneous users simultaneously.
论文通过相关的信源网络联合编码技术解决了可分级码流的保护和自适应问题，将其用于同时面向异构用户的流媒体鲁棒传输。
The proposed fine granularity scalable video coding algorithm has low computational complexity.
本文研究实现的细粒度视频分层编码算法计算复杂度较低。
The proposed fine granularity scalable video coding algorithm has low computational complexity.
本文研究实现的细粒度视频分层编码算法计算复杂度较低。
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