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Computational Imaging Prediction of Starburst-Effect Diffraction Spikes.

ABSTRACT: When imaging bright light sources, rays of light emanating from their centres are commonly observed; this ubiquitous phenomenon is known as the starburst effect. The prediction and characterization of starburst patterns formed by extended sources have been neglected to date. In the present study, we propose a novel trichromatic computational framework to calculate the image of a scene viewed through an imaging system with arbitrary focus and aperture geometry. Diffractive light transport, imaging sensor behaviour, and implicit image adjustments typical in modern imaging equipment are modelled. Characterization methods for key optical parameters of imaging systems are also examined. Extensive comparisons between theoretical and experimental results reveal excellent prediction quality for both focused and defocused systems.

SUBMITTER: Lendermann M

PROVIDER: S-EPMC6240111 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Computational Imaging Prediction of Starburst-Effect Diffraction Spikes.

Lendermann Markus M Tan Joel Shi Quan JSQ Koh Jin Ming JM Cheong Kang Hao KH

Scientific reports 20181116 1

When imaging bright light sources, rays of light emanating from their centres are commonly observed; this ubiquitous phenomenon is known as the starburst effect. The prediction and characterization of starburst patterns formed by extended sources have been neglected to date. In the present study, we propose a novel trichromatic computational framework to calculate the image of a scene viewed through an imaging system with arbitrary focus and aperture geometry. Diffractive light transport, imagin ...[more]

PMID: 30446668

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