English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

An optical imaging system forms an object image by recollecting lightscattered by the object. However, intact optical information of the objectdelivered through the imaging system is deteriorated by imperfect opticalelements and unwanted defects. Image deconvolution, also known as inversefiltering, has been widely exploited as a recovery technique because of itspractical feasibility, and operates by assuming the linear shift-invariantproperty of the imaging system. However, shift invariance is not rigorouslyhold in all imaging situations and it is not a necessary condition for solvingthe inverse problem of light propagation. Here, we present a method to solvethe linear inverse problem of coherent light propagation without assuming shiftinvariance. Full characterization of imaging capability of the system isachieved by successively recording optical responses, using various laserillumination angles which are systematically controlled by a digitalmicro-mirror device. Experimental results show that image distortions caused byoptical defocus can be restored by conventional deconvolution, but severeaberrations produced by a tilted lens or an inserted disordered layer can becorrected only by the proposed generalized image deconvolution. This workgeneralizes the theory of optical imaging and deconvolution, and enablesdistortion-free imaging under any general imaging condition.

Generalized image deconvolution by exploiting spatially variant point spread functions