DocumentCode :
2958844
Title :
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
Link To Document :
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