Computational optical imaging: challenges, opportunities, new trends, and emerging applications

Abstract

Computational imaging technology (CIT), with its many variations, addresses the limitations of industrial design. CIT can effectively overcome the bottlenecks in physical information acquisition, model development, and resolution by being tightly coupled with mathematical calculations and signal processing in information acquisition, transmission, and interpretation. Qualitative improvements are achieved in the dimensions, scale, and resolution of the information. Therefore, in this review, the concepts and meaning of CIT are summarized before establishing a real CIT system. The basic common problems and relevant challenging technologies are analyzed, particularly the non-linear imaging model. The five typical imaging requirements–distance, resolution, applicability, field of view, and system size–are detailed. The corresponding key issues of super-large-aperture imaging systems, imaging beyond the diffraction limit, bionic optics, interpretation of light field information, computational optical system design, and computational detectors are also discussed. This review provides a global perspective for researchers to promote technological developments and applications.