Super-Resolution Multilayer Structure Analysis via Depth Adaptive Compressed Sensing for Terahertz Subsurface Imaging

Super-resolution subsurface imaging based on sparse regularization is presented in assuming the terahertz (THz) band multilayer structure analysis. The THz wave subsurface imaging with
$\mu $
-scale spatial resolution and penetration depth are promising for several applications, such as nondestructive testing and chemical/biomedical compound analyses. The sparse regularization-based compressed sensing (CS) approach has considerable potential to provide super-resolution subsurface imaging in a time-of-flight estimation. However, using optical lens-based measurements, e.g., THz time-domain spectroscopic (THz-TDS) systems, a depth resolution is highly dependent on the depth of each layer, which becomes more critical in the out-of-focus case. This study demonstrated that the above depth-dependence could be solved by using an appropriate depth-dependent reference signal, by using the THz-TDS measured data.