NDLI: Adaptive difference of Gaussians to improve subsurface 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	In detection of landmines using ground penetrating radar (GPR), the most significant interference is the specular reflection. Compared with the specular reflection, landmine scattered signals are of small amplitude and difficult to observe. Better detection results can be obtained if the specular reflection can be well separated from the landmine scattered signals. Difference of Gaussians (DOG) is an operation that generates a sharp image from an original image, i.e. in the case of a GPR image, it keeps the specular reflection intact. Therefore by subtracting the DOG output from an original GPR image, we are able to remove the specular reflection and enhance the landmine scattered signals. The DOG takes the difference between two Gaussian curves of zero means and different standard deviations and convolves with the original image. One advantage of the DOG is that the two standard deviations can be chosen properly to suit different applications. We develop an adaptive DOG (ADOG) to process GPR images to improve detection of buried landmines. In the ADOG, the two standard deviations of Gaussians are computed adaptively as a GPR image is scanned from the top to the bottom row. At each row, two windows are used to calculate the two standard deviations and the current row is convolved with the DOG. The output has an unchanged specular reflection while there is a reduced landmine scattered signal. The final image is obtained by subtracting the ADOG output from the original image to remove the specular reflection. The landmine scattered signal is greatly enhanced, allowing more accurate detection.
Sponsorship	IEEE IEEE Geosci. & Remote Sensing Soc. Canadian Remote Sensing Soc. Univ. Waterloo Natural Resources Canada (NRCan) Canadian Space Agency (CSA) Environ. Canada NASA Nat. Oceanic & Atmos. Adm. (NOAA) Office of Naval Res.(ONR) Nat. Space Dev. Agency of Japan (NASDA) Nat. Polar-orbiting Environ. Satellite Syst. (NPOESS)
Starting Page	3441
Ending Page	3443
File Size	234803
Page Count	3
File Format	PDF
ISBN	078037536X
DOI	10.1109/IGARSS.2002.1027209
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-06-24
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gaussian processes Landmine detection Laplace equations Scattering Ground penetrating radar Reflection Gaussian approximation Convolution
Content Type	Text
Resource Type	Article

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