Generalized image deconvolution by exploiting spatially variant point spread functions
SangYun Lee, Kyeoreh Lee, Seungwoo Shin, YongKeun Park

TL;DR
This paper introduces a generalized image deconvolution method that effectively restores images distorted by optical aberrations, even under non-shift-invariant conditions, expanding the capabilities of optical imaging systems.
Contribution
It presents a novel deconvolution approach that does not assume shift invariance, allowing correction of complex optical distortions in imaging systems.
Findings
Successfully restores images with severe aberrations
Handles optical distortions beyond shift-invariant assumptions
Enables distortion-free imaging under various conditions
Abstract
An optical imaging system forms an object image by recollecting light scattered by the object. However, intact optical information of the object delivered through the imaging system is deteriorated by imperfect optical elements and unwanted defects. Image deconvolution, also known as inverse filtering, has been widely exploited as a recovery technique because of its practical feasibility, and operates by assuming the linear shift-invariant property of the imaging system. However, shift invariance is not rigorously hold in all imaging situations and it is not a necessary condition for solving the inverse problem of light propagation. Here, we present a method to solve the linear inverse problem of coherent light propagation without assuming shift invariance. Full characterization of imaging capability of the system is achieved by successively recording optical responses, using various…
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Taxonomy
TopicsRandom lasers and scattering media · Digital Holography and Microscopy · Advanced Optical Imaging Technologies
