Share Email Print
cover

Proceedings Paper

Compression of AIRS data using Emperical Mode Decomposition
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

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.

Paper Details

Date Published: 14 October 2004
PDF: 11 pages
Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); doi: 10.1117/12.558967
Show Author Affiliations
Irina Gladkova, National Oceanic and Atmospheric Administration/CREST (United States)
CUNY/City College (United States)
Leonid Roytman, National Oceanic and Atmospheric Administration/CREST (United States)
CUNY/City College (United States)
Mitchell D. Goldberg, National Oceanic and Atmospheric Administration/NESDIS (United States)
John Weber, National Oceanic and Atmospheric Administration/CREST (United States)
CUNY/City College (United States)


Published in SPIE Proceedings Vol. 5548:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective
Hung-Lung Allen Huang; Hal J. Bloom, Editor(s)

© SPIE. Terms of Use
Back to Top