An adaptive seed point selection technique for segmentation of polarimetric synthetic aperture radar images

Author

Chaudhuri, Sanjay D. ; Singh, Mrigendra Pratap ; Mishra, Anadi

Author_Institution

Defence Electron. Applic. Lab., Dehradun, India

fYear

2013

fDate

9-11 Dec. 2013

Firstpage

21

Lastpage

26

Abstract

The performance of the most popular unsupervised clustering algorithm, k-means depends on the initial seed points. This paper proposes a mode based adaptive seed selection algorithm, which is used to improve the performance of Wishart segmentation for the segmentation of polarimetric synthetic aperture radar images.

Keywords

image segmentation; pattern clustering; radar imaging; radar polarimetry; synthetic aperture radar; Wishart segmentation; adaptive seed point selection; adaptive seed selection; image segmentation; k-means clustering; polarimetric synthetic aperture radar images; seed points; unsupervised clustering algorithm; Algorithm design and analysis; Clustering algorithms; Conferences; Histograms; Image segmentation; Remote sensing; Synthetic aperture radar; Wishart distance; cluster validity; mode; polarimetric SAR; seed point; synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Information Processing (ICIIP), 2013 IEEE Second International Conference on

Conference_Location

Shimla

Print_ISBN

978-1-4673-6099-9

Type

conf

DOI

10.1109/ICIIP.2013.6707548

Filename

6707548