Cluster-Based Split-Window Radon Transform Algorithm for Ship Wake Detection

Author

Na-na, Liu ; Jing-wen, Li ; Yan-feng, Cui

Author_Institution

Sch. of Electron. & Inf. Eng., BeiHang Univ., Beijing, China

Volume

5

fYear

2009

fDate

March 31 2009-April 2 2009

Firstpage

773

Lastpage

777

Abstract

The purpose of this article is to present a novel algorithm for ship wake detection in synthetic aperture radar (SAR) images. The main originality of our work is that splitting the image with small window before conventional Radon transform to make the illumination has stronger consistency in each window and adopting clustering algorithm to select real wakes form disturbing lines. Experimental result on real SAR image is presented and compared to that obtained using conventional approaches.

Keywords

Radon transforms; feature extraction; marine radar; oceanographic techniques; pattern clustering; radar detection; radar imaging; ships; synthetic aperture radar; wakes; SAR; cluster-based split-window Radon transform algorithm; linear feature detection; ship wake detection; synthetic aperture radar image; Clustering algorithms; Computer science; Computer vision; Data processing; Gravity; Lighting; Marine vehicles; Radar detection; Synthetic aperture radar; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Information Engineering, 2009 WRI World Congress on

Conference_Location

Los Angeles, CA

Print_ISBN

978-0-7695-3507-4

Type

conf

DOI

10.1109/CSIE.2009.521

Filename

5170638