Compression of AIRS data using empirical mode decomposition

被引：2

作者：

Gladkova, I ^{[1
]}

Roytman, L ^{[1
]}

Goldberg, M ^{[1
]}

Weber, J ^{[1
]}

机构：

[1] CUNY City Coll, NOAA, CREST, New York, NY 10031 USA

来源：

ATMOSPHERIC AND ENVIRONMENTAL REMOTE SENSING DATA PROCESSING AND UTILIZATION: AN END TO END SYSTEM PERSPECTIVE | 2004年 / 5548卷

关键词：

compression; empirical mode decomposition; intrinsic mode functions; Karhunen-Loeve;

D O I：

10.1117/12.558967

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

In this paper, we consider an application of the Empirical Mode Decomposition (EMD) introduced by Norden E. Huang in 1996 to the compression of 3D hyperspectral sounding data. The EMD is a new data analysis method which is based on expansion of the data in terms of Intrinsic Mode Functions (IMF). These IMFs are based on and derived from the data set. Since EMD adaptively represent the signal as a sum of "well behaved" amplitude/frequency modulated components, we found it very well suited for the whitening part of the compression scheme.

引用

页码：88 / 98

页数：11

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