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Exemplar-based image inpainting using structure consistent patch matching

delete2017-12-01
delete37
PRE
AI
王
王海霞 (Haixia Wang)
L
Li Jiang
R
Ronghua Liang *
X
Xiaoxin Li
DOI:10.1016/j.neucom.2016.08.149delete
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Abstract

Abstract

En 中文
Image inpainting restores lost or deteriorated parts of images according to the information of known regions. Criminisi has proposed an effective exemplar-based inpainting method, which has the advantages of both texture synthesis and diffusion-based inpainting. Yet, it has its own flaws of fast priority dropping and visual inconsistency. In this paper, we propose a space varying updating strategy for the confidence term and a matching confidence term to improve the filling priority estimation. We propose structure consistent patch matching to take the distribution of source and target patch differences into account. Fast Fourier transform is adapted for full image searching to achieve better and faster matching results. Experimental results are given to demonstrate the improvements made by our proposed method. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Image inpainting
Exemplar-based
Patch matching
Fast Fourier transform
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

Z
zhejiang university of technology
Scholars:
3.3W
Papers: 2.0W
Citations: 22
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