DocumentCode :
2073817
Title :
Edge detection in multispectral remote sensing images
Author :
Sirin, Tuba ; Saglam, Mehmet Izzet ; Erer, Isin ; Gokmen, Muhittin ; Ersoy, Okan
Author_Institution :
Informatics Inst., Istanbul Tech. Univ., Turkey
fYear :
2005
fDate :
9-11 June 2005
Firstpage :
529
Lastpage :
533
Abstract :
In this paper, we discuss edge detection by first using a clustering algorithm followed by a known edge detection filter such as Canny or generalized edge detector (GED). We developed a new clustering method called Self-Organizing Global Ranking (SOGR). Comparative results with multispectral satellite images including SOGR, SOM and K Means clustering methods are discussed. The results show that the two-stage algorithms are better than single stage edge detector algorithms.
Keywords :
edge detection; geophysical signal processing; pattern clustering; remote sensing; Canny detector; SOGR; SOM; clustering algorithm; clustering method; edge detection; generalized edge detector; k-means; multispectral remote sensing images; multispectral satellite images; self-organizing global ranking; two-stage algorithms; Biomembranes; Clustering algorithms; Clustering methods; Detectors; Filters; Image edge detection; Image segmentation; Informatics; Laplace equations; Remote sensing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances in Space Technologies, 2005. RAST 2005. Proceedings of 2nd International Conference on
Print_ISBN :
0-7803-8977-8
Type :
conf
DOI :
10.1109/RAST.2005.1512625
Filename :
1512625
Link To Document :
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