Abstract
Time-resolved terahertz spectroscopic imaging has become a powerful tool for material identification and non-invasive imaging in recent years. However, this technique is generally suffered from the long data acquisition time. This study proposes a novel 3-D tensor-based compressive sensing model for terahertz single-pixel imaging systems. Unlike traditional systems that only use peak values for image pattern analysis, the proposed system can be used to derive the complete terahertz pulse information for refraction index analysis. Because this 3-D model can compress the terahertz response in both spatial and time domains in a tensor compressive sensing format, it can significantly reduce signal reconstruction time and facilitate rapid material identification.