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:2002
卷号:XXXIV Part 3 A
页码:73-78
出版社:Copernicus Publications
摘要:In this paper we present a new classification technique for segmenting remotely sensed images, based on cluster analysis and machine learning. Traditional segmentation techniques which use clustering require human interaction to fine-tune the clustering algorithm parameters and select good clusters. Our technique applies inductive learning techniques using C4.5 to learn the parameters and pick good clusters automatically. The techniques are demonstrated on level 1 of RAIL, a hierarchical road recognition system we have developed
关键词:Classification; Edge; GIS; High Resolution; Identification; Land Use; Segmentation; Spatial Infrastructures