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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2013.2261308
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|a eng
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| 100 |
1 |
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|a Le Meur, Olivier
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Hierarchical super-resolution-based inpainting
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|c 2013
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 01.04.2014
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|a Date Revised 02.09.2013
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a This paper introduces a novel framework for examplar-based inpainting. It consists in performing first the inpainting on a coarse version of the input image. A hierarchical super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of computational complexity and visual quality. However, to be less sensitive to the parameter setting of the inpainting method, the low-resolution input picture is inpainted several times with different configurations. Results are efficiently combined with a loopy belief propagation and details are recovered by a single-image super-resolution algorithm. Experimental results in a context of image editing and texture synthesis demonstrate the effectiveness of the proposed method. Results are compared to five state-of-the-art inpainting methods
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| 650 |
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|a Journal Article
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1 |
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|a Ebdelli, Mounira
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Guillemot, Christine
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 22(2013), 10 vom: 01. Okt., Seite 3779-90
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|x 1941-0042
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|g volume:22
|g year:2013
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|g pages:3779-90
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|u http://dx.doi.org/10.1109/TIP.2013.2261308
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