Hierarchical super-resolution-based inpainting

Olivier Le Meur 1 Mounira Ebdelli 1 Christine Guillemot 1
1 Sirocco - Analysis representation, compression and communication of visual data
Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : 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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Article dans une revue
IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2013, 22 (10), pp.3779-3790. <10.1109/TIP.2013.2261308>



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Olivier Le Meur, Mounira Ebdelli, Christine Guillemot. Hierarchical super-resolution-based inpainting. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2013, 22 (10), pp.3779-3790. <10.1109/TIP.2013.2261308>. <hal-00876168>

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