.png){kind=icon}
返回
Toward optimality in scalable predictive coding
.png){kind=icon}
PRE
AI
DOI：10.1109/83.931091.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A method is proposed for efficient scalability in predictive coding, which overcomes known fundamental shortcomings of the prediction loop at enhancement layers. The compression efficiency of an enhancement-layer is substantially improved by casting the design of its prediction module within an estimation-theoretic framework, and thereby exploiting all information available at that layer fur the prediction of the signal, and encoding of the prediction error. While the most immediately important application is in video compression, the method is derived in a general setting and is applicable to any scalable predictive coder. Thus, the estimation-theoretic approach is first developed for basic DPCM compression and demonstrates the power of the technique in a simple setting that only involves straightforward prediction, scalar quantization, and entropy coding, Results for the scalable compression of first-order Gauss-Markov and Laplace-Markov signals illustrate the performance. A specific estimation algorithm is then developed for standard scalable DCT-based video coding. Simulation results show consistent and substantial performance gains due to optimal estimation at the enhancement-layers.
Keyword:
STOCHASTIC STABILITY
VIDEO
QUANTIZATION
SCHEMES
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
暂无机构信息
引用论文
Design with Nature: Key lessons from McHarg's intrinsic suitability in the wake of Hurricane Sandy
PREAI
分享收藏Different patterns of cortical activity in females and males during spatial long-term memory.png)
NeuroImage
NeuroImageIF0
PREAI
分享收藏Stereoselective synthesis of optically active dictyopterenes A and B and their geometrical isomers.
OAAI
OAAI分享收藏
查看更多内容