dc.contributor.author | Lucat, Antoine | en_US |
dc.contributor.author | Hegedus, R. | en_US |
dc.contributor.author | Pacanowski, Romain | en_US |
dc.contributor.editor | Reinhard Klein and Holly Rushmeier | en_US |
dc.date.accessioned | 2017-09-21T07:15:07Z | |
dc.date.available | 2017-09-21T07:15:07Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 978-3-03868-035-2 | |
dc.identifier.issn | 2309-5059 | |
dc.identifier.uri | http://dx.doi.org/10.2312/mam.20171329 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/mam20171329 | |
dc.description.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 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 gives better results than common deconvolution techniques and the uncertainty values (convolution kernel and noise) of the algorithm output are recovered. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | I.3.3 [Computer Graphics] | |
dc.subject | Picture/Image Generation | |
dc.subject | Line and curve generation | |
dc.title | Diffraction Prediction in HDR Measurements | en_US |
dc.description.seriesinformation | Workshop on Material Appearance Modeling | |
dc.description.sectionheaders | Acquisition Issues | |
dc.identifier.doi | 10.2312/mam.20171329 | |
dc.identifier.pages | 29-33 | |