Super resolution reconstruction method for time-of-flight range data using complex compressive sensing

This paper addresses the reconstruction of complex sparse measurements taken from a complex valued signal, whose phase carries important information. This is the case in time-of-flight (TOF) and terahertz imaging, where the phase corresponds to the distance and thickness of objects, respectively. We used a single pixel TOF camera setup showing that existing state-of-the-art methods have problems to reconstruct the phase information as no prior knowledge is included. We present a method which includes prior knowledge of the phase signal in the reconstruction process by solving a minimization problem with a total variation regularization in phase space and show that this approach leads to superior super-resolution reconstruction results for TOF range data.