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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2073817