Improved SAR target detection via extended fractal features

Author

Kaplan, Lance M.

Author_Institution

Clark Atlanta Univ., GA, USA

Volume

37

Issue

2

fYear

2001

fDate

4/1/2001 12:00:00 AM

Firstpage

436

Lastpage

451

Abstract

The utility of the extended fractal (EF) feature is evaluated for the enhancement of the focus of attention (FOA) stage of a synthetic aperture radar (SAR) automatic target recognition (ATR) system. Unlike more traditional SAR detection features that distinguish target pixels from the background only on the basis of contrast, the EF feature is sensitive to both the contrast and size of objects. Furthermore, the structure for the EF feature computational algorithm lends itself to very fast implementation, and it can be shown that the new feature has a CFAR-like (constant false alarm rate) property. We demonstrate the improved performance using the new feature by testing a number of different detection approaches over two databases of SAR imagery

Keywords

feature extraction; fractals; radar imaging; radar target recognition; synthetic aperture radar; SAR imaging; SAR target detection; automatic target recognition; computational algorithm; constant false alarm rate; extended fractal feature; focus of attention; synthetic aperture radar; Computer vision; Focusing; Fractals; Image databases; Object detection; Radar detection; Spatial databases; Synthetic aperture radar; Target recognition; Testing;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.937460

Filename

937460