DocumentCode
3427861
Title
Transform methods for remote sensing environmental monitoring
Author
Chen, Chi Hau
Author_Institution
Electr. & Comput. Eng. Dept., Univ. of Massachusetts Dartmouth, Dartmouth, MA
fYear
2008
fDate
March 31 2008-April 4 2008
Firstpage
5165
Lastpage
5168
Abstract
Transform methods in signal and image processing generally speaking are easy to use and can play a number of useful roles in remote sensing environmental monitoring. Examples are the pollution and forest fire monitoring. Transform methods offer effective procedures to derive the most important information for further processing or human interpretation and to extract important features for pattern classification. Most transform methods are used for image (or signal) enhancement and compression. However other transform methods are available for linear or nonlinear discrimination in the classification problems. In this paper we will examine the major transform methods which are useful for remote sensing especially for environmental monitoring problems. Many challenges to signal processing will be reviewed. Computer results are shown to illustrate some of the methods discussed.
Keywords
data compression; environmental management; feature extraction; image enhancement; remote sensing; signal classification; transforms; classification problems; feature extraction; forest fire monitoring; nonlinear discrimination; pattern classification; pollution monitoring; remote sensing environmental monitoring; signal compression; signal enhancement; transform methods; Data mining; Feature extraction; Fires; Humans; Image coding; Image processing; Pattern classification; Pollution; Remote monitoring; Signal processing; SAR image noise; component analysis; contextual image models; environmental monitoring; transform methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location
Las Vegas, NV
ISSN
1520-6149
Print_ISBN
978-1-4244-1483-3
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2008.4518822
Filename
4518822
Link To Document