Diffraction Prediction in HDR 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
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]
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
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
< Reduce
Melting the frontiers between Light, Shape and Matter [MANAO]
Laboratoire Photonique, Numérique et Nanosciences [LP2N]
Language
en
Communication dans un congrès avec actes
This item was published in
EUROGRAPHICS WORKSHOP ON MATERIAL APPEARANCE MODELING, 2017-06-18, Helsinki. 2017
English Abstract
Modern imaging techniques have proved to be very efficient to recover a scene with high dynamic range values. However, this high dynamic range can introduce star-burst patterns around highlights arising from the diffraction ...Read more >
Modern imaging techniques have proved to be very efficient to recover a scene with high dynamic range 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 predicts, from a closed-form PSF, where the diffraction will affect the pixels of an HDR image, making it possible to discard them from the measurement. Our results give better results than common deconvolution techniques and the uncertainty values (convolution kernel and noise) of the algorithm output are recovered.Read less <
ANR Project
Reproduction de textures d'objets d'art ancien à base de micro-géométrie - ANR-15-CE38-0005
Origin
Hal imported