The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation

Yan Jinwen; Sun Hui; Zhang Shenghua

doi:null

您当前的位置：

首页 >

文章列表页 >

The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation

更新时间：2020-08-12

- The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation
- Optics and Precision Engineering Vol. 5, Issue 5, Pages: 30-35(1997)
- 作者机构：
  
  1. 长春邮电学院通信工程系, 长春, 130012
  2. 中国科学院长春光学精密机械研究所长春,130022
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Received：12 August 1996，
  
  Published Online：15 October 1997，
  
  Published：15 October 1997
- 稿件说明：
移动端阅览
阎敬文, 孙辉, 张圣华. 基于 Karhunen-leove 变换的多光谱数据压缩统计特性分析[J]. 光学精密工程, 1997,(5): 30-35

Yan Jinwen, Sun Hui, Zhang Shenghua. The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation[J]. Editorial Office of Optics and Precision Engineering, 1997,(5): 30-35
阎敬文, 孙辉, 张圣华. 基于 Karhunen-leove 变换的多光谱数据压缩统计特性分析[J]. 光学精密工程, 1997,(5): 30-35 DOI：

Yan Jinwen, Sun Hui, Zhang Shenghua. The Characteristic Properties Analysis for Multispectral Data Compression Based on Karhunen-Leove Transformation[J]. Editorial Office of Optics and Precision Engineering, 1997,(5): 30-35 DOI：

摘要

提出了基于Karhunen-leove变换(KLT)的多光谱图像数据压缩方法

并对多光谱图像数据KLT统计特征进行了分析。在对KLT进行了理论推导后

如何将该方法应用于实际多光谱数据压缩系统进行了分析讨论。研究提出了一种最大限度地减少额外码流开销的方法。实验结果表明:该方法对16光谱段的三维数据可获得3.2～5.3的压缩比

且几乎没有失真

明显优于用DCT去除谱相关性的方法。

Abstract

In this paper a compression method for multispectral image data basedon Karhunen-Leove Transformation (KLT) was presented

and the statistical properties of multispectral image using KLT was analyzed. After deducing the theoryof KLT

we discussed the schemes of applying this method to the practical compression system of multispectral image data. A maxium degree decreasing bit flow method is researched and presented. Experiment results shows that this methodcan obtain the compression ratio 3.2～5.3 for sixteen band multispectral

almostlossless. It is superior to the method of applying DCT to remove the spectral correlation .

关键词

Keywords

references

Views

320

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Compressive tracking algorithm combining online feature selection with covariance matrix

Dynamic rate control for CCSDS nearly lossless compression of multispectral remote image

Prediction of visual discomfort of stereoscopic images based on saliency analysis

Assessment of storage reliability for FOGs by multivariate degradation data

2-D attitude measurement of object based on covariance matrix

Related Author

Can-feng LI

Hong-ying ZHANG

ZHANG Lei

LI Xian

WU Hong-song

SHEN Ji

PU Jian-fu

FENG Shu-yi

Related Institution

College of Electronic Information and Automation, Civil Aviation University of China

Shanghai Aerospace Electronic Technology Institute

Shenyang Aerospace University

Faculty of Information Science and Engineering, Ningbo University

北京航空航天大学仪器科学与光电工程学院

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰