• 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