Literature DB >> 29092194

Diffraction effects detection for HDR image-based measurements.

A Lucat, R Hegedus, R Pacanowski.   

Abstract

Modern imaging techniques have proved to be very efficient to recover a scene with high dynamic range (HDR) values. However, this high dynamic range can introduce star-burst patterns around highlights arising from the diffraction of the camera aperture. The spatial extent of this effect can be very wide and alters pixels values, which, in a measurement context, are not reliable anymore. To address this problem, we introduce a novel algorithm that, utilizing a closed-form PSF, predicts where the diffraction will affect the pixels of an HDR image, making it possible to discard them from the measurement. Our approach gives better results than common deconvolution techniques and the uncertainty values (convolution kernel and noise) of the algorithm output are recovered.

Entities:  

Year:  2017        PMID: 29092194     DOI: 10.1364/OE.25.027146

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  1 in total

1.  Computational Imaging Prediction of Starburst-Effect Diffraction Spikes.

Authors:  Markus Lendermann; Joel Shi Quan Tan; Jin Ming Koh; Kang Hao Cheong
Journal:  Sci Rep       Date:  2018-11-16       Impact factor: 4.379

  1 in total

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