Title :
Knowledge-based segmentation of Landsat images
Author :
Ton, Jezching ; Sticklen, Jon ; Jain, Anil K.
Author_Institution :
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
fDate :
3/1/1991 12:00:00 AM
Abstract :
A knowledge-based approach for Landsat image segmentation is proposed. The image segmentation problem is solved by extracting kernel information from the input image to provide an initial interpretation of the image and by using a knowledge-based hierarchical classifier to discriminate between major land-cover types in the study area. The proposed method is designed in such a way that a Landsat image can be segmented and interpreted without any prior image-dependent information. The general spectral land-cover knowledge is constructed from the training land-cover data, and the road information of an image is obtained through a road-detection program
Keywords :
computerised pattern recognition; computerised picture processing; geophysical techniques; geophysics computing; knowledge based systems; remote sensing; Landsat; computer method; geophysical technique; hierarchical classifier; image segmentation; kernel information; knowledge-based approach; land surface remote sensing; land-cover types; road-detection program; Computer science; Data mining; Expert systems; Image generation; Image segmentation; Kernel; Reflectivity; Remote sensing; Satellites; Training data;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
