Diffraction effects detection for HDR image-based measurements
LUCAT, Antoine
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
PACANOWSKI, Romain
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
LUCAT, Antoine
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
PACANOWSKI, Romain
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
< Reduce
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Melting the frontiers between Light, Shape and Matter [MANAO]
Language
en
Article de revue
This item was published in
Optics Express. 2017-10-20, vol. 25, n° 22, p. 2921 - 2929
Optical Society of America - OSA Publishing
English 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 ...Read more >
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.Read less <
English Keywords
(1001830) Deconvolution
(1000100) Image processing
(0501940) Diffraction
OCIS codes: (1200120) Instrumentation
measurement
and metrology
(0501220) Apertures
ANR Project
Reproduction de textures d'objets d'art ancien à base de micro-géométrie - ANR-15-CE38-0005
Origin
Hal imported