Fuzzy C-means and principal component analysis based GPR image enhancement

Author

Riaz, M.M. ; Ghafoor, Abdul ; Sreeram, Victor

Author_Institution

Dept. of Electr. Eng., Nat. Univ. of Sci. & Technol. (NUST), Islamabad, Pakistan

fYear

2013

fDate

April 29 2013-May 3 2013

Firstpage

1

Lastpage

4

Abstract

In this paper, a ground penetrating radar image enhancement scheme based on fuzzy c-means and principal component analysis is proposed. The original image is decomposed into clutter, noise and target subspaces using principal component analysis. Fuzzy c-means is used to assign weights to different subspaces based on their membership values. Simulation results demonstrate that the proposed scheme can detect (single and multiple) targets, provide better mean square error and peak signal to noise ratio.

Keywords

fuzzy set theory; ground penetrating radar; image enhancement; mean square error methods; principal component analysis; radar imaging; fuzzy c-means; ground penetrating radar image enhancement scheme; mean square error; membership values; peak signal to noise ratio; principal component analysis based GPR image enhancement; target subspaces; Clutter; Eigenvalues and eigenfunctions; Ground penetrating radar; Image enhancement; PSNR; Principal component analysis; Fuzzy C-Means; Ground Penetrating Radar; Image Enhancement; Principal Component Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference (RADAR), 2013 IEEE

Conference_Location

Ottawa, ON

ISSN

1097-5659

Print_ISBN

978-1-4673-5792-0

Type

conf

DOI

10.1109/RADAR.2013.6585987

Filename

6585987