Improving GPR Imaging of the Buried Water Utility Infrastructure by Integrating the Multidimensional Nonlinear Data Decomposition Technique into the Edge Detection

Abstract

Although ground-penetrating radar (GPR) is effective to detect shallow-buried objects, it still needs more effort for the application to investigate a buried water utility infrastructure. Edge detection is a well-known image processing technique that may improve the resolution of GPR images. In this study, we briefly review the theory of edge detection and discuss several popular edge detectors as examples, and then apply an enhanced edge detecting method to GPR data processing. This method integrates the multidimensional ensemble empirical mode decomposition (MDEEMD) algorithm into standard edge detecting filters. MDEEMD is implemented mainly for data reconstruction to increase the signal-to-noise ratio before edge detecting. A quantitative marginal spectrum analysis is employed to support the data reconstruction and facilitate the final data interpretation. The results of the numerical model study followed by a field example suggest that the MDEEMD edge detector is a competent method for processing and interpreting GPR data of a buried hot spring well, which cannot be efficiently handled by conventional techniques. Moreover, the proposed method should be readily considered a vital tool for processing other kinds of buried water utility infrastructures.

Algorithm Fusion for 3D Ground-Penetrating Radar Imaging with Field Examples

“…Since the original GPR traces acquired in the field are one-dimensional, it may not be practical to employ multidimensional EEMD [39,41] filtering techniques. In light of our previous research [6,41,45,49,55,62] and personal experiences, we performed a technical survey and compared the test results of the advanced multidimensional EEMD technique and the proposed methodology before carrying out this research. The algorithm fusion technique had a much lower computational cost with an acceptable outcome.…”

“…Figure 14b shows the 2D profile of L1 (Figure 14a) processed using the conventional method, and the result of applying the NLT EEMD method is demonstrated in Figure 14c. The pass-band of the linear filter used in the conventional method was determined by referring to the marginal spectrum [6,21,45,49,62] of the selected component. The bandwidth of a 500 MHz center frequency GPR system is between 250 MHz and 750 MHz.…”

Hand geometry recognition: an approach for closed and separated fingers

“…They are used in images to filter out parts of an image. Canny edge algorithm is a common edge detection algorithm and it is credited as an optimal edge detector [14], [15]. The three criteria that Canny edge detection satisfies include low error rate, great localization and single response.…”