Towards unifying diffusion and exemplar-based inpainting

A novel framework for image inpainting is proposed, relying on graph-based diffusion processes. Depending on the construction of the graph, both flow-based and exemplar-based inpainting methods can be implemented by the same equations, hence providing a unique framework for geometry and texture-based approaches to inpainting. Furthermore, the use of a variational framework allows to overcome the usual sensitivity of exemplar-based methods to the heuristic issues by providing an evolution criterion. The use of graphs also makes our framework more flexible than former non-local variational formulations, allowing for example to mix spatial and non-local constraints and to use a data term to provide smoother blending between the initial image and the result.


Published in:
2010 Ieee International Conference On Image Processing, 417-420
Presented at:
IEEE International Conference on Image Processing - ICIP 2010, Hong Kong, People's Republic of China, September 26-20, 2010
Year:
2010
Publisher:
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa
ISBN:
978-1-4244-7994-8
Keywords:
Laboratories:




 Record created 2010-05-31, last modified 2018-09-13

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