Title :
Transform methods for remote sensing environmental monitoring
Author_Institution :
Electr. & Comput. Eng. Dept., Univ. of Massachusetts Dartmouth, Dartmouth, MA
fDate :
March 31 2008-April 4 2008
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;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4518822