# Fusing Ground-Penetrating Radar Images for Improving Image Characteristics Fidelity
## 5 Methodology and Experimental Results  
In the actual procedure, as demonstrated in Figure 6, two of the images are read and prepared for data processing by initially mirroring one of them horizontally to be able to fit the other one and find dimensional similarities. Key regions of interest are extracted from both images, and the 2D Fourier Transform (FFT) is applied to analyze their frequency content. Pattern recognition techniques are then applied by thresholding the images and using LBP for texture analysis. Finally, the processed data are combined to perform reconstruction and highlight important features of the subsurface. The subsequent sections will analyze each step, from image pre-processing and FFT application to pattern recognition and the final image reconstruction. When receiving and recording the excessive responses that arise in the process of subsurface investigation with GPR technology, it is understood that the correct and appropriate processing of these data is required so that the interpretation of the subsurface analysis is more detailed and accurate. For this purpose, during the scanning process with the GPR, two images of the same examined path were taken in the present work, the first in one direction and the second in the opposite direction. This procedure was performed for each path so that we had a pair of scans in a different direction. For better illustration, in Figure 7, a piece of the path at Panagopoula's scan is shown as the initial length of the image is 21,688 pixels. Figure 6: Block diagram of the pre-processing and GPR image analysis procedures. Figure 7: The forward direction scan (**left**) and the reverse direction scan (**right**) of the area are shown here. These scans reveal subsurface structures, providing detailed insights into the geological features of the Panagopoula region. A comparison of both scan directions helps in validating the consistency and accuracy of the detected subsurface features. The captured images represent the reflectance data from the underground structures in the area. The two \"versions\" of the image, as will be analyzed below, can help to compare symmetrical patterns and/or to align and compose the two for further analysis. Upon visual comparison of the images and due to the large extent of the path, various footprints from various underground objects and artifacts can be seen. Based on this, the image is inspected to identify ROIs, which will be selected to perform the proposed processing method that will be analyzed. The ROI is chosen to be some excess response from the total captured, as defined in Figure 8.  
The proposed method consists of the following processing steps of the data with the aim of extracting GPR patterns from the ROI and then to be able to identify from the subsidiary image many hyperbolic responses, facilitating the researcher in the targeted discrimination of excessive peaks, which also demonstrates the existence of some buried object or water table etc. Because each shot is also plagued by ringing or objects that may overlap with each other, it usually becomes difficult to distinguish hyperbolic peaks from the overall image. The extracted pattern is approximately hyperbolic in shape (Figure 9) and the evaluation of the Fourier transform is carried out. The Fourier transform helps in the analysis of the frequency components and can reveal periodic structures, such as hyperbolic responses. A binary pattern is created based on the intensity values of the ROI, and through appropriate thresholding, regions with specific intensity values that highlight a hyperbolic shape pattern are isolated (Figure 9). We then  
Figure 8: The regions of interest of the two scans. (**a**) The ROI of the forward direction of [PERSON]’s scan to be used to export patterns. (**b**) The ROI of the backward direction of [PERSON]’s scan to be used to export patterns. Figure 9: (**a**) The binary pattern extraction from a hyperbolic response will serve as the initial input for the subsequent LBP analysis from the forward scan.