# Intelligent Recognition of Road Internal Void Using Ground-Penetrating Radar
## 3 Results
### Research on Preprocessing Techniques for Internal Void Images in Road
#### 3.1.2 Image Quality Degradation and Enhancement  
In practical scenarios, images of voids inside roads captured using GPR are affected by factors such as signal attenuation, noise interference, equipment resolution, and the complexity of the underground medium. These factors lead to instability in the quality  
Figure 4: Comparison before and after image filling. and clarity of the images. Therefore, research into image quality enhancement techniques is necessary. Typically, supervised learning processes require paired datasets, which comprise input images of low quality and target images of high quality. However, in the field, high-quality images corresponding to the low-quality images of voids inside roads are lacking, which hampers the learning process and renders supervised learning methods inapplicable. Unsupervised learning, on the other hand, mainly relies on analyzing the intrinsic structure and patterns within the data itself, independent of paired label data. However, it suffers from a lack of intuitiveness and a clear optimization goal, leading to unstable improvements in image quality and an inability to guarantee achieving the desired quality level. Based on these challenges, this study proposes a method for constructing void image data aimed at supervised learning. This method primarily generates low-quality and high-quality images by degrading and enhancing the image quality, respectively, based on images collected in the field. When identifying void areas within road interior radar images, the information at the image edges is particularly important as it can be used to determine the precise location, shape, size, and distribution of the void areas. In the image processing phase, the high-frequency information in an image can reflect details such as image feature characteristics, target area edges, and spatial changes. Therefore, during the process of image quality degradation, emphasis will be placed on processing the high-frequency information characteristics of the image. Fourier transform low-pass filtering is a technique used in the frequency domain to process images. It can be used to diminish and remove high-frequency elements in an image while retaining the low-frequency elements, thus achieving the goal of image quality degradation. When collecting images of road interiors using 3D GPR, various types of noise are encountered. Electromagnetic interference noise mainly originates from electromagnetic waves in the surrounding environment, which can disrupt the reception of radar signals. Random noise is typically generated by the electronic components of the radar equipment itself, influenced by the quality of equipment manufacturing and external environmental factors. System noise includes noises produced by reflections and scatterings within the radar system, originating from radar wave reflections at the interfaces between different mediums. Echo blurring occurs due to the multi-directional scattering of radar waves during transmission, leading to the overlapping and blurring of echo signals, making it difficult to discern image details. The presence of these noises reduces the quality of the images. Gaussian filtering is effective at decreasing image noise through image smoothing while preserving edge information without damaging the edges. The effects of image quality degradation and image quality enhancement are illustrated in Figure 5.  
From Figure 5a, it can be observed that the void area displays alternating black and white highlighted regions. This is due to the dielectric constant at the void being lower than the surrounding materials, causing strong reflections of electromagnetic waves in this area. The image colors in non-void areas are relatively uniform, with some areas appearing  
Figure 5: Image quality degradation and enhancement. The red box area is the key comparison area. wavy, which is caused by the inhomogeneity of the road medium and the differences in the propagation of electromagnetic waves through it.