Ground Penetrating Radar (GPR), as a non-destructive detection technology, has been widely used in infrastructure construction, tunneling, agriculture and forestry. It has the advantages of fast detection speed, high accuracy and non-destructive detection. However, GPR is often affected by the interference of subsurface media when facing complex geological environments, resulting in low contrast, high noise and clutter interference in the acquired B-scan images, which seriously affects the detection of subsurface structures and imaging performance. In order to improve the quality of images acquired by GPR in mixed soil media, this paper proposes HE-R2M (Histogram Equalization with Remapping and Morphology) image enhancement algorithm for preprocessing B-Scan images with respect to B-scan hyperbolic features of underground targets. The algorithm is based on the histogram equalization algorithm to initially enhance the image, and for the B-Scan image features, combined with the histogram interval remapping method and morphological processing, it can successfully suppress the clutter features in the B-Scan image while retaining the effective information of the hyperbola. The effectiveness and robustness of the algorithm are verified through simulation and real experiments. The proposed HE-R2M image preprocessing algorithm provides a potential idea for the application expansion of GPR, and offers an effective solution to improve the performance of underground structure detection and imaging.
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Chen et al. (2024) studied this question.
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