Abstract:  Ground penetrating radar(GPR) threedimensional imaging, known as Cscan imaging, often suffers from limited information dimensionality and subjective image quality. In this study, the authors explore two critical imaging parameters, the valid measurement threshold and information transformation function, to formulate an optimization strategy for GPR Cscan imaging. Furthermore, the authors assess image quality using structural similarity and peak signaltonoise ratio as evaluation metrics. To quantify the effectiveness of different imaging parameters, a case study is conducted involving indoor reinforced concrete walls and road surfaces. The experimental findings indicate that, for typical urban GPR applications, an optimal measurement threshold of 70% coupled with the mean method as the transformation function provides the best results. Moreover, an attribute imaging method that combines amplitude and frequency is proposed to enhance the information within Cscan images. This integrated visualization approach accurately portrays the geometric characteristics of target objects while reducing noise interference in GPR Cscan imaging. These enhancements are advantageous in minimizing human interpretation errors and enhancing the overall reliability of Cscan interpretation.

Key words: ground penetrating radar, Cscan, multiattribute imaging, visualization optimization, urban infrastructure inspection