A new article is available in IPOL: http://www.ipol.im/pub/art/2017/189/
Alasdair Newson, Andrés Almansa, Yann Gousseau, and Patrick Pérez,
Non-Local Patch-Based Image Inpainting,
Image Processing On Line, 7 (2017), pp. 373–385.
https://doi.org/10.5201/ipol.2017.189
Abstract
Image inpainting is the process of filling in missing regions in an
image in a plausible way. In this contribution, we propose and describe
an implementation of a patch-based image inpainting algorithm. The
method is actually a two-dimensional version of our video inpainting
algorithm proposed in [A. Newson et al., Video inpainting of complex
scenes, SIAM Journal of Imaging Sciences, 7 (2014)]. The algorithm
attempts to minimize a highly non-convex functional, first introducted
by Wexler et al. in [Wexler et al., Space-time video completion, CCVPR
(2004)]. The functional specifies that a good solution to the inpainting
problem should be an image where each patch is very similar to its
nearest neighbor in the unoccluded area. Iterations are performed in a
multi-scale framework which yields globally coherent results. In this
manner two of the major goals of image inpainting, the correct
reconstruction of textures and structures, are addressed. We address a
series of important practical issues which arise when using such an
approach. In particular, we reduce execution times by using the
PatchMatch [C. Barnes, PatchMatch: a randomized correspondence algorithm
for structural image editing, ACM Transactions on Graphics, (2009)]
algorithm for nearest neighbor searches, and we propose a modified patch
distance which improves the comparison of textured patches. We address
the crucial issue of initialization and the choice of the number of
pyramid levels, two points which are rarely discussed in such
approaches. We provide several examples which illustrate the advantages
of our algorithm, and compare our results with those of state-of-the-art
methods.
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