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.
© 2008 Optical Society of America
Full Article | PDF ArticleMore Like This
M. Dirk Robinson and David G. Stork
Appl. Opt. 47(10) B11-B20 (2008)
Zeqing Yu, Qiangbo Zhang, Xiao Tao, Yong Li, Chenning Tao, Fei Wu, Chang Wang, and Zhenrong Zheng
Opt. Express 30(22) 40871-40883 (2022)
Jiangyong Li, Lin Zhao, Xiaoqin Wu, Fei Liu, Yazhe Wei, Chun Yu, and Xiaopeng Shao
Appl. Opt. 61(20) 5916-5925 (2022)