Thomas Bugnon
École Polytechnique Fédérale de Lausanne
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Featured researches published by Thomas Bugnon.
color imaging conference | 2008
Thomas Bugnon; Mathieu Brichon; Roger D. Hersch
The Yule-Nielsen modified spectral Neugebauer model enables predicting reflectance spectra from surface coverages. In order to provide high prediction accuracy, this model is enhanced with an ink spreading model accounting for physical dot gain. Traditionally, physical dot gain, also called mechanical dot gain, is modeled by one ink spreading curve per ink. An ink spreading curve represents the mapping between nominal to effective dot surface coverages when an ink halftone wedge is printed. In previous publications, we have shown that using one ink spreading curve per ink is not sufficient to accurately model physical dot gain, and that the physical dot gain of a specific ink is modified by the presence of other inks. We therefore proposed an ink spreading model taking all the ink superposition conditions into account. We now show that not all superposition conditions are useful and necessary when working with cyan, magenta, yellow, and black inks. We therefore study the influence of ink spreading in different superposition conditions on the accuracy of the spectral prediction model. Finally,
color imaging conference | 2007
Thomas Bugnon; Mathieu Brichon; Roger D. Hersch
The Yule-Nielsen modified Spectral Neugebauer reflection prediction model enhanced with an ink spreading model provides high accuracy when predicting reflectance spectra from ink surface coverages. In the present contribution, we try to inverse the model, i.e. to deduce the surface coverages of a printed color halftone patch from its measured reflectance spectrum. This process yields good results for cyan, magenta, and yellow inks, but unstable results when simultaneously fitting cyan, magenta, yellow, and black inks due to redundancy between these four inks: black can be obtained by printing either the black ink or similar amounts of the cyan, magenta, and yellow inks. To overcome this problem, we use the fact that the black pigmented ink absorbs light in the infrared domain, whereas cyan, magenta, and yellow inks do not. Therefore, with reflection spectra measurements spanning both the visible and infrared domain, it is possible to accurately deduce the black ink coverage. Since there is no redundancy anymore, the cyan, magenta, yellow, and pigmented black ink coverages can be recovered with high accuracy.
IEEE Transactions on Image Processing | 2011
Thomas Bugnon; Roger D. Hersch
Todays spectral reflection prediction models are able to predict the reflection spectra of printed color images with an accuracy as high as the reproduction variability allows. However, to calibrate such models, special uniform calibration patches need to be printed. These calibration patches use space and have to be removed from the final product. The present contribution shows how to deduce the ink spreading behavior of the color halftones from spectral reflectances acquired within printed color images. Image tiles of a color as uniform as possible are selected within the printed images. The ink spreading behavior is fitted by relying on the spectral reflectances of the selected image tiles. A relevance metric specifies the impact of each ink spreading curve on the selected image tiles. These relevance metrics are used to constrain the corresponding ink spreading curves. Experiments performed on an inkjet printer demonstrate that the new constraint-based calibration of the spectral reflection prediction model performs well when predicting color halftones significantly different from the selected image tiles. For some prints, the proposed image based model calibration is more accurate than a classical calibration.
Journal of Electronic Imaging | 2012
Thomas Bugnon; Roger D. Hersch
The Yule-Nielsen modified spectral Neugebauer model (YNSN) enables predicting reflectance spectra from ink surface coverages of halftones. In order to provide an improved prediction accuracy, this model is enhanced with an ink spreading model accounting for ink spreading in all superposition conditions (IS-YNSN). As any other spectral reflection prediction model, the IS-YNSN model is conceived to predict the reflection spectra of color-constant patches. Instead of color-constant patches, we investigate if tiles located within color images can be accurately predicted and how they can be used to facilitate the calibration of the ink spreading model. In the present contribution, we detail an algorithm to automatically select image tiles as uniform as possible from color images by relying on their CMY or CMYK pixel values. The tile selection algorithm incorporates additional constraints relying on surface coverages of the inks. We demonstrate that an ink spreading model calibrated with as few as 5 to 10 optimally chosen image tiles allows the corresponding YNSN model to provide accurate spectral predictions.
Proceedings of SPIE | 2011
Thomas Bugnon; Roger D. Hersch
The Yule-Nielsen modified spectral Neugebauer model (YNSN) enables predicting reflectance spectra from ink surface coverages of halftones. In order to provide an improved prediction accuracy, this model is enhanced with an ink spreading model accounting for ink spreading in all superposition conditions (IS-YNSN). As any other spectral reflection prediction model, the IS-YNSN model is conceived to predict the reflection spectra of uniform patches. Instead of uniform patches, we investigate if tiles located within color images can be accurately predicted and how they can be used to facilitate the calibration of the ink spreading model. In the present contribution, we first detail an algorithm to automatically select image tiles as uniform as possible from color images by relying on the CMY or CMYK pixel values of these color tiles. We show that if these image tiles are uniform enough, they can be accurately predicted by the IS-YNSN model. The selection algorithm incorporates additional constraints and is verified on 6 different color images. We finally demonstrate that the ink spreading model can be calibrated with as few as 5 to 10 image tiles.
color imaging conference | 2010
Romain Rossier; Thomas Bugnon; Roger D. Hersch
Journal of Imaging Science and Technology | 2009
Roger D. Hersch; Mathieu Brichon; Thomas Bugnon; Mathieu Hébert
Color Research and Application | 2009
Roger D. Hersch; Mathieu Brichon; Thomas Bugnon; Peter Amrhyn; Frederique Crete; Safer Mourad; Hebert Janser; Yufan Jiang; Matthias Riepenhoff
Archive | 2007
Roger D. Hersch; Edoardo Charbon; Thomas Bugnon; Patrick Emmel
color imaging conference | 2008
Fabrice Rousselle; Thomas Bugnon; Roger D. Hersch