Preprocessing Remotely-sensed Data for Ecient Analysis and Classiication

نویسندگان

  • Patrick M Kelly
  • James M White
چکیده

Interpreting remotely sensed data typically requires expensive specialized computing machinery capable of stor ing and manipulating large amounts of data quickly In this paper we present a method for accurately analyzing and categorizing remotely sensed data on much smaller less expensive platforms Data size is reduced in such a way as to retain the integrity of the original data where the format of the resultant data set lends itself well to providing an e cient interactive method of data classi cation

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تاریخ انتشار 1993