title: Optimized compressive sampling for passive millimeter-wave imaging.
abstract: In this paper, we briefly describe a single detector passive millimeter-wave imaging system, which has been previously presented. The system uses a cyclic sensing matrix to acquire incoherent measurements of the observed scene and then reconstructs the image using a Bayesian approach. The cyclic nature of the sensing matrix allows for the design of a single unified and compact mask that provides all the required random masks in a convenient way, such that no mechanical mask exchange is needed. Based on this setup, we primarily propose the optimal adaptive selection of sampling submasks out of the full cyclic mask to obtain improved reconstruction results. The reconstructed images show the feasibility of the imaging system as well as its improved performance through the proposed sampling scheme.
authors.affiliation: Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, Illinois 60208, USA. leonidasspinoulas2015@u.northwestern.edu
authors.forename: Leonidas
authors.initials: L
authors.lastname: Spinoulas
authors.forename: Jin
authors.initials: J
authors.lastname: Qi
authors.forename: Aggelos K
authors.initials: AK
authors.lastname: Katsaggelos
authors.forename: Thomas W
authors.initials: TW
authors.lastname: Elmer
authors.forename: Nachappa
authors.initials: N
authors.lastname: Gopalsami
authors.forename: Apostolos C
authors.initials: AC
authors.lastname: Raptis