AUTHOR=Li Zhilong , Zuo Jian , Zhao Yuanmeng , Han Zhongde , Xu Zhihao , Zhao Yunzhang , Yang Chao , Hu Weidong , Zhang Cunlin TITLE=A Novel Method for the Enhancement of Composite Materials’ Terahertz Image Using Unsharp Masking and Guided Filtering Technology JOURNAL=Frontiers in Physics VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2021.750588 DOI=10.3389/fphy.2021.750588 ISSN=2296-424X ABSTRACT=

When terahertz imaging technology is used for the nondestructive testing of composite materials, the signal is often affected by the experimental environment and internal noise of the system, as well as the absorption and scattering effect of the tested materials. The obtained image has degradation phenomena such as low contrast, poor resolution of small targets and blurred details. In order to improve the image quality, this paper proposes a novel method for the enhancement of composite materials’ terahertz image by using unsharp masking and guided filtering technology. The method includes the processing steps of hard threshold shrinkage denoising based on discrete wavelet transform, amplitude imaging, unsharp masking, guided filtering, contrast stretching, and pseudo-color mapping. In this paper, these steps are reasonably combined and optimized to obtain the final resulting image. To verify the effectiveness of the proposed method, a 150–220 GHz high frequency terahertz frequency modulated radar imaging system was used to image three commonly used sandwich structure composites, and the enhancement processing were carried out. The resulting images with significantly enhanced contrast, detail resolution and edge information were obtained, and the prefabricated defects were all detected; Five objective evaluation indexes including standard deviation, mean gradient, information entropy, energy gradient and local contrast were used to compare and analyze the processing results of different image enhancement methods. The subjective and objective evaluation results showed that the proposed method can effectively suppress the noise in terahertz detection signals, enhance the ability of defect detection and positioning, and improve the accuracy of detection. The proposed method in this paper is expected to play a positive role in improving the practicability of terahertz imaging detection technology and expanding its application fields.