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The increasing need of restoring high-resolution Hyper-Spectral (HS) imagesis determining a growing reliance on Computer Vision-based processing toenhance the clarity of the image content. HS images can, in fact, suffer fromdegradation effects or artefacts caused by instrument limitations. This paperfocuses on a procedure aimed at reducing the degradation effects,frequency-dependent blur and noise, in Terahertz Time-Domain Spectroscopy(THz-TDS) images in reflection geometry. It describes the application of ajoint deblurring and denoising approach that had been previously proved to beeffective for the restoration of THz-TDS images in transmission geometry, butthat had never been tested in reflection modality. This mode is often the onlyone that can be effectively used in most cases, for example when analyzingobjects that are either opaque in the THz range, or that cannot be displacedfrom their location (e.g., museums), such as those of cultural interest.Compared to transmission mode, reflection geometry introduces, however, furtherdistortion to THz data, neglected in existing literature. In this work, wesuccessfully implement image deblurring and denoising of both uniform-shapesamples (a contemporary 1 Euro cent coin and an inlaid pendant) and sampleswith the uneven reliefs and corrosion products on the surface which make theanalysis of the object particularly complex (an ancient Roman silver coin). Thestudy demonstrates the ability of image processing to restore data in the 0.25- 6 THz range, spanning over more than four octaves, and providing thefoundation for future analytical approaches of cultural heritage using thefar-infrared spectrum still not sufficiently investigated in literature.

Beam-Shape Effects and Noise Removal from THz Time-Domain Images in Reflection Geometry in the 0.25-6 THz Range