期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：1992
卷号：XXIX Part B3
页码：484-487
出版社：Copernicus Publications
摘要：The aim of this research is to compare the performance ( probability of misclassification) of several object classifiers ( some of them developed by author) and classical per-pixelmaximum likelihood classifier for forest ( deciduous, coniferous and mixed) classification.The new analytical method ( derived by author) is applied for the selection of object classifierbased on calculating the probability of misclassification.Object classifiers are supervised maximum likelihood classifiers incorporating spatial characteristicsof an image during classification based on Markov random field model.The research is carried out on Landsat TM data received from IFAG, Frankfurt a.M.During investigation the Image Analysis and Classification System IMAX ( developed byauthor and his group ) is used.First results show the complexity of the problem and the need for further investigation
关键词：Thematic information extraction; Spatial characteristics of images; Pattern;recognition; Landsat TM.
