Title :
Decomposing GPR images in a variation approach
Author :
Huang, Yishuo ; Lin, Shang-Yuh ; Yang, Jie-Chun ; Wu, Shengmin
Author_Institution :
Dept. of Constr. Eng., Choayang Univ. of Technol., Taichung, Taiwan
Abstract :
Interpreting a ground penetration radar (GPR) image is an important task in research into subsurface conditions. In a GPR image, noise usually obscures the weak reflections, especially for objects buried at deep locations. The discrete wavelet transform has been recognized as an efficient tool for depressing noise effects appearing in a GPR image. Another approach is the total variation (TV) de-noising model, which was first introduced by Rudin, Osher, and Fatemi in 1992. This paper uses the TV de-noising model to remove noise from GPR images. By computing the signal-to-noise ratios, the performances of the discrete wavelet de-noising and TV de-noising models are evaluated. From the experimental results, the TV de-noising model offers an efficient, numerically stable, and robust way to deal with noise present in a GPR image.
Keywords :
discrete wavelet transforms; geophysical image processing; ground penetrating radar; image denoising; radar imaging; remote sensing by radar; GPR image decomposition; GPR image noise; TV denoising model; discrete wavelet denoising; discrete wavelet transform; ground penetrating radar; noise effect depression; signal-noise ratio; subsurface conditions; total variation denoising model; variation approach; weak reflections; Computational modeling; Gold; Ground penetrating radar; Noise; Noise reduction; Numerical models; TV; GPR Image; Total Variation; Wavelet Transform;
Conference_Titel :
Ground Penetrating Radar (GPR), 2012 14th International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-2662-9
DOI :
10.1109/ICGPR.2012.6254826