Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging.
In this dual-blind deconvolution (DBD) problem, the receiver admits a multi-carrier wireless communications signal that is overlaid with the radar signal reflected off multiple targets.
Specifically, we propose to jointly optimize an optical architecture for acquiring a single coded light field snapshot and a convolutional neural network (CNN) for estimating the disparity maps.
no code implementations • 27 Jun 2022 • Henry Arguello, Jorge Bacca, Hasindu Kariyawasam, Edwin Vargas, Miguel Marquez, Ramith Hettiarachchi, Hans Garcia, Kithmini Herath, Udith Haputhanthri, Balpreet Singh Ahluwalia, Peter So, Dushan N. Wadduwage, Chamira U. S. Edussooriya
The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task.
When the radar receiver is not collocated with the transmitter, such as in passive or multistatic radars, the transmitted signal is also unknown apart from the target parameters.
Compressive imaging using coded apertures (CA) is a powerful technique that can be used to recover depth, light fields, hyperspectral images and other quantities from a single snapshot.