NDLI: Adaptive difference of Gaussians to improve subsurface object detection using GPR imagery

Content Provider	IEEE Xplore Digital Library
Author	Xiaoyin Xu Miller, E.L.
Copyright Year	2002
Description	Author affiliation: Center for Subsurface Sensing & Imaging Syst., Northeastern Univ., Boston, MA, USA (Xiaoyin Xu; Miller, E.L.)
Abstract	We present an adaptive difference of Gaussians (ADOG) method to improve landmine detection from ground penetrating radar (GPR) imagery. GPR is widely used for a variety of subsurface sensing problems including landmine detection and localization. In most all applications, specular reflection from the air-ground interface is the most significant source of interference often eclipsing the returns from the buried object. From an image processing viewpoint, the specular reflection constitutes a sharp edge and the landmine reflected signals are more smooth and of low spatial frequency. As an edge-preserving method, the ADOG keeps the specular reflection intact and removes the object reflected signals. Then by subtracting the ADOG output from the original image, we eliminate the specular reflection and obtain an image with enhanced object reflected signals. Using the difference image, we can obtain better result in detecting buried objects. Results from applying our algorithm on a landmine detection application are used to demonstrate the performance of the method.
Sponsorship	IEEE Signal Process. Soc
File Size	364963
File Format	PDF
ISBN	0780376226
ISSN	15224880
DOI	10.1109/ICIP.2002.1039986
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-09-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gaussian processes Object detection Ground penetrating radar Landmine detection Reflection Buried object detection Image edge detection Interference Image processing Signal processing
Content Type	Text
Resource Type	Article

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