Title :
Spatiospectral cluster analysis of elongated regions in aerial imagery
Author :
Agouris, P. ; Doucette, Peter ; Stefanidis, Anthony
Author_Institution :
Dept. of Spatial Inf. Eng., Maine Univ., Orono, ME, USA
Abstract :
The extraction of road networks from digital imagery is a fundamental operation in geospatial applications. In images captured by new satellite sensors with a ground sample distance of less than 2 meters per pixel, roads can be broadly described as elongated regions. We introduce a novel technique of spatiospectral cluster analysis in which the spatial properties of elongated regions are identified from unsupervised analysis of their corresponding spectral properties. Preliminary results demonstrate a fully automated process in which road centerline topology can be identified in high-resolution aerial imagery in the presence of typical clutter
Keywords :
clutter; feature extraction; image processing; pattern clustering; remote sensing; spectral analysis; automated process; clutter; digital imagery; elongated regions; geospatial applications; ground sample distance; high-resolution aerial imagery; multispectral image experiments; road centerline topology; road networks extraction; satellite sensors; spatiospectral cluster analysis; spectral properties; unsupervised analysis; Automation; Data mining; Humans; Image analysis; Image edge detection; Image resolution; Intelligent networks; Layout; Pixel; Roads;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.958612
