Abstract
Non-line-of-sight (NLOS) imaging has aroused great interest during the past few years, by providing a unique solution for the observation of hidden objects behind obstructions or scattering media. As such, NLOS imaging may facilitate broad applications in autonomous driving, remote sensing, and medical diagnosis. However, existing NLOS frameworks suffer from severe degradation of resolution and signal-to-noise ratio (SNR) due to aberrations induced by scattering media and system misalignment, restricting its practical applications. This paper proposes a computational adaptive optics (CAO) method for NLOS imaging to correct optical aberrations in post-processing without the requirement of any hardware modifications. We demonstrate the effectiveness of CAO with a confocal NLOS imaging system in Terahertz (THz) band by imaging different samples behind occlusions for both low- and high-order aberrations. With appropriate metrics used for iterative CAO in post-processing, both the resolution and SNR can be increased by several times without reducing the data acquisition speed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
