Diffraction effects detection for HDR image-based measurements

Antoine Lucat 1, 2 Ramon Hegedus 3 Romain Pacanowski 2, 1
1 MANAO - Melting the frontiers between Light, Shape and Matter
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, LP2N - Laboratoire Photonique, Numérique et Nanosciences
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.
Document type :
Journal articles
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-01637417
Contributor : Antoine Lucat <>
Submitted on : Wednesday, March 21, 2018 - 9:46:45 AM
Last modification on : Thursday, October 11, 2018 - 5:30:02 PM

Identifiers

Citation

Antoine Lucat, Ramon Hegedus, Romain Pacanowski. Diffraction effects detection for HDR image-based measurements. Optics Express, Optical Society of America, 2017, 25 (22), pp.2921 - 2929. ⟨10.1364/OE.25.027146⟩. ⟨hal-01637417⟩

Share

Metrics

Record views

450

Files downloads

112