Abstract-Characterizing the Layer Structures of the Lacquerware From the Palace Museum by Terahertz Imaging in Reflection Geometry

                                                       

Hongfei Zhang, Yuanmeng Zhao, Chenyu Li, Cunlin Zhang

https://www.frontiersin.org/articles/10.3389/fphy.2021.751205/full

Chinese lacquerware is an important invention of arts and crafts in China. In this study, Chinese lacquerware is characterized using terahertz reflectometric imaging. The lacquerware studied herein comprises an ornamental wood panel covered by multiple layers of lacquers to portray motifs. For characterizing lacquerware, a terahertz time-domain spectroscopic reflectometric imaging system is proposed. The role of the proposed terahertz imaging system in highlighting the interface between layers during stratigraphic buildup in reflection geometry is proved. The proposed system provides a universal method for assessing the structural information of lacquered objects in a contactless and non-invasive manner; moreover, it provides two-dimensional images, subsurface three-dimensional images, and stratigraphic images (b-scans) in a contactless and non-invasive manner. Using the proposed system, we examine the buried layers of the lacquerware, including faults in the wooden layer and damages in the lacquerware. Research shows the promising prospects of terahertz time-domain spectroscopic reflectometric imaging as a non-destructive detection technique suited to lacquerware.

Abstract-Using Markov constraint and constrained least square filter to develop a novel method of passive terahertz image restoration

Yuanmeng Zhao, Xiao Sun, Cunlin Zhang, Yuejin Zhao,

https://iopscience.iop.org/article/10.1088/1742-6596/1187/4/042094

In recent years, passive terahertz imaging has gained significant attention in both research and practice. One big challenge with passive terahertz imaging is its low-quality images with high level of noise. State-of-the art image restoration methods have been developed for image denoising, such as methods based on Markov constraint and regular filter methods. Building upon these two methods, this paper develops a novel method for passive terahertz image restoration which preserves well both high frequency and low frequency information of the images. Performance of our method is evaluated using two common image criteria of the image sharpness, i.e. edge intensity and definition. Experimental results showed our method outperform state-of-the art methods for passive terahertz image restoration.