Title :
Task-specific segmentation of remote sensing images
Author :
Xuan, Jianhua ; Adali, Tülay
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Maryland Univ., Baltimore, MD, USA
Abstract :
Presents a task-specific segmentation method that incorporates semantic knowledge into data-driven segmentation process through different region merge scores. Starting from a simple region growing algorithm which results in over-segmented regions, the authors apply a region merging method designed specifically for each task such as road extraction or vegetation area identification. Further, edge information is integrated to verify and correct region boundaries. The experimental results show that this method can reliably extract areas of interest such as roads and vegetation areas in Landsat images
Keywords :
geophysical signal processing; geophysical techniques; image segmentation; remote sensing; Landsat image; data-driven segmentation process; edge information; feature extraction; geophysical measurement technique; image processing; image region analysis; image segmentation; land surface; optical imaging; over-segmented regions; region growing algorithm; region merge score; region merging method; remote sensing; road extraction; semantic knowledge; task specific segmentation; terrain mapping; vegetation area identification; vegetation mapping; Computer science; Data mining; Image edge detection; Image segmentation; Merging; Remote sensing; Rivers; Roads; Satellites; Vegetation mapping;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
DOI :
10.1109/IGARSS.1996.516447