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.
Knowledge-based segmentation of Landsat images
Wissensbasierende Aufteilung von Landsat-Bildern
IEEE Transactions on Geoscience and Remote Sensing ; 29 , 2 ; 222-232
1991
11 Seiten, 39 Quellen
Aufsatz (Zeitschrift)
Englisch
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