Method of Tree Radar Signal Processing Based on Curvelet Transform

Ground penetrating radar has been widely applied on geological disaster surveys, road investigations, bridge health monitoring, and other subsurface surveys. Many studies introduced this method on tree non-destructive detection. However, as for the complicated internal structure of tree trunk, the radargram of tree always have the problems of complicated recognition, low signal noise ratio (SNR) and images hardly to be explained. To get a clear photo and a high signal noise ratio, this paper applied the Curvelet transform to wipe out the noise to extract the characteristics of signal and to improve the signal noise ratio. As a comparative, the wavelet transform is also used to de-noise as well. The SNR of Curvelet transform is large than wavelet transform both in simulated data and real tree radar data. And the image of the one which was processed by Curvelet transform is clearer than processed by wavelet transform. The result shows that the Curvelet transform is suitable for processing the tree radar image with many curve characteristics. And this study provides an important foundation of further radar image processing.