A new approach for landmine discrimination in SAR images

Author

Yu-Ming Wang ; Qian Song ; Han-hua Zhang ; Xiao-tao Huang ; Zhi-min Zhou

Author_Institution

Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China

fYear

2012

fDate

9-11 Nov. 2012

Firstpage

1

Lastpage

4

Abstract

Landmine detection is an available application of Synthetic Aperture Radar (SAR). According to the double-hump structure of a landmine in SAR images, a new approach is proposed for landmine discrimination with sparse representation. First, the total variation (TV) algorithm is used to denoise. Second, a sub-dictionary is obtained within the narrow limits of the Gabor dictionary. Third, the sparse reconstruction mean square error (MSE) is calculated for classification. The experimental results indicate that the proposed approach is effective for landmine discrimination.

Keywords

dictionaries; image classification; image reconstruction; image representation; image sensors; landmine detection; mean square error methods; radar imaging; synthetic aperture radar; Gabor dictionary; MSE; SAR imaging; TV algorithm; double-hump structure; image classification; image denoising; landmine detection discrimination; mean square error; sparse representation; synthetic aperture radar; total variation algorithm; Clutter; Dictionaries; Feature extraction; Image reconstruction; Landmine detection; Synthetic aperture radar; TV; Mean Square Error (MSE); Total Variation (TV); landmine detection; sparse representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Signal Processing (IASP), 2012 International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-2547-9

Type

conf

DOI

10.1109/IASP.2012.6425019

Filename

6425019