Highly Corrupted Image Inpainting Through Hypoelliptic Diffusion

被引:8
|
作者
Boscain, Ugo V. [1 ,2 ]
Chertovskih, Roman [3 ,4 ]
Gauthier, Jean-Paul [5 ]
Prandi, Dario [6 ]
Remizov, Alexey O. [7 ]
机构
[1] UPMC Univ Paris 06, CNRS, Lab Jacques Louis Lions, F-75005 Paris, France
[2] INRIA, INRIA Team CAGE, Paris, France
[3] Univ Porto, Res Ctr Syst & Technol, Fac Engn, Rua Dr Roberto Frias S-N, P-4200465 Porto, Portugal
[4] Samara Natl Res Univ, 34 Moskovskoye Ave, Samara 443086, Russia
[5] Univ Toulon USTV, LSIS, UMR CNRS 7296, F-83957 La Garde, France
[6] Cent Supelec, CNRS, L2S, 3 Rue Joliot Curie, F-91192 Gif Sur Yvette, France
[7] CMAP Ecole Polytech, CNRS, F-91128 Palaiseau, France
基金
欧洲研究理事会;
关键词
Image reconstruction; Inpainting; Sub-Riemannian hypoelliptic diffusion; INVARIANT PARABOLIC EVOLUTIONS; INVERTIBLE ORIENTATION SCORES; CONTOUR ENHANCEMENT; RECONSTRUCTION; FRAMEWORK; EQUATIONS; FIELDS; SE(2);
D O I
10.1007/s10851-018-0810-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present a new biomimetic image inpainting algorithm, the Averaging and Hypoelliptic Evolution (AHE) algorithm, inspired by the one presented in Boscain et al. (SIAM J. Imaging Sci. 7(2):669-695, 2014) and based upon a semi-discrete variation of the Citti-Petitot-Sarti model of the primary visual cortex V1. The AHE algorithm is based on a suitable combination of sub-Riemannian hypoelliptic diffusion and ad hoc local averaging techniques. In particular, we focus on highly corrupted images (i.e., where more than the 80% of the image is missing), for which we obtain high-quality reconstructions.
引用
收藏
页码:1231 / 1245
页数:15
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