title: Computational imaging systems: joint design and end-to-end optimality.
abstract: A framework is proposed for optimal joint design of the optical and reconstruction filters in a computational imaging system. First, a technique for the design of a physically unconstrained system is proposed whose performance serves as a universal bound on any realistic computational imaging system. Increasing levels of constraints are then imposed to emulate a physically realizable optical filter. The proposed design employs a generalized Benders' decomposition method to yield multiple globally optimal solutions to the nonconvex optimization problem. Structured, closed-form solutions for the design of observation and reconstruction filters, in terms of the system input and noise autocorrelation matrices, are presented. Numerical comparison with a state-of-the-art optical system shows the advantage of joint optimization and concurrent design.
authors.affiliation: Department of Electrical Engineering, Southern Methodist University , Dallas, TX 75275-0338, USA. tmirani@engr.smu.edu
authors.forename: Tejaswini
authors.initials: T
authors.lastname: Mirani
authors.forename: Dinesh
authors.initials: D
authors.lastname: Rajan
authors.forename: Marc P
authors.initials: MP
authors.lastname: Christensen
authors.forename: Scott C
authors.initials: SC
authors.lastname: Douglas
authors.forename: Sally L
authors.initials: SL
authors.lastname: Wood