Clutter removal in GPR images using non-negative matrix factorization

ABSTRACT

Ground-penetrating radar (GPR) is a commonly used high-resolution electromagnetic technique for subsurface imaging which has many applications such as landmine, cable and pipes detection. It is well known that the clutter presented in the GPR images deteriorates the image quality and decreases the performance of the target detection methods, especially for shallowly buried targets. To deal with this issue, we propose a new clutter removal method based on the low-rank approximation of the GPR image by non-negative matrix factorization (NMF). The proposed method is applied to real GPR images as well as to a realistic dataset provided by the new version of the electromagnetic software simulation tool gprMax. The visual and quantitative results obtained for different scenarios containing different soils, surfaces, burial depths and target types validate the effectiveness of the proposed method over the widely used state-of-the-art clutter removal methods.

KEYWORDS:

• Non-negative matrix factorization
• gprMax
• ground-penetrating radar
• image decomposition
• clutter removal
• electromagnetic simulation

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Deniz Kumlu

Mr. Deniz Kumlu received the M.S. degree from the Ming Hsieh Department of Electrical Engineering, University of Southern California (USC), Los Angeles, CA, USA, in 2012. He is currently working toward the Ph.D. degree in the Department of Electronics and Communications Engineering, Istanbul Technical University (ITU), Istanbul, Turkey. He is currently working as an instructor at National Defense University/Naval Academy. His research interests include remote sensing, image and statistical signal processing.

Isin Erer

Dr Isin Erer received B.Sc., M.S., and Ph.D. degrees from Istanbul Technical University (ITU), Istanbul, Turkey, in 1991, 1993, and 2001, respectively, all in electrical and electronics engineering. Currently, she is an associate professor with the Department of Electronics and Communications, ITU. Her research interests include statistical signal processing, high-resolution radar imaging, spectral estimation, and multidimensional linear prediction techniques. She has been author of several journal and conference papers in the area of high-resolution radar imaging techniques and clutter removal in GPR images. Dr. Erer is a member of IEEE Geoscience Society.