Robust entropy-guided image segmentation for ground detection in GPR

Identifying the ground within a ground penetrating radar (GPR) image is a critical component of automatic and assisted target detection systems. As these systems are deployed to more challenging environments they encounter rougher terrain and less-ideal data, both of which can cause standard ground detection methods to fail. This paper presents a means of improving the robustness of ground detection by adapting a technique from image processing in which images are segmented by local entropy. This segmentation provides the rough location of the air-ground interface, which can then act as a “guide” for more precise but fragile techniques. The effectiveness of this two-step “coarse/fine” entropyguided detection strategy is demonstrated on GPR data from very rough terrain, and its application beyond the realm of GPR data processing is discussed.