Introduction to compressive sampling and applications in THz imaging

Abstract

The Compressive Sensing (CS) is an emergent theory that provides an alternative to Shannon/Nyquist Sampling Theorem. By CS, a sparse signal can be perfectly recovered from a number of measurements, which is significantly lower than the number of periodic samples required by Sampling Theorem. The THz radiation is nowadays of high interest due to its capability to emphasize the molecular structure of matter. In imaging applications, one of the problems is the sensing device: the THz detectors are slow and bulky and cannot be integrated in large arrays like the CCD. The CS can provide an efficient solution for THz imaging. This solution is the single pixel camera with CS, a concept developed at Rice University that has materialized in several laboratory models and an IR camera released on the market in 2013. We reconsidered this concept in view of THz application and, at present, we have an experimental model for a THz camera. The paper has an extended section dedicated to the CS theory and single pixel camera architecture. In the end, we briefly presents the hardware and software solutions of our model, some characteristics and a first image obtained in visible domain.