Computational imaging systems: joint design and end-to-end optimality |
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Authors: | Mirani Tejaswini Rajan Dinesh Christensen Marc P Douglas Scott C Wood Sally L |
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Affiliation: | Department of Electrical Engineering, Southern Methodist University , Dallas, TX 75275-0338, USA. tmirani@engr.smu.edu |
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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. |
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