Geometrically Guided Exemplar-Based Inpainting

被引:69
作者
Cao, Frederic [1 ]
Gousseau, Yann [2 ]
Masnou, Simon [3 ]
Perez, Patrick [4 ]
机构
[1] DxO Labs, F-92100 Boulogne, France
[2] Telecom ParisTech, LTCI, CNRS, F-75013 Paris, France
[3] Univ Lyon 1, CNRS, Inst Camille Jordan UMR 5208, F-69622 Villeurbanne, France
[4] Technicolor Corp Res, Rennes Lab, F-35576 Cesson Sevigne, France
关键词
inpainting; texture synthesis; exemplar-based inpainting; level lines; image geometry; Euler spirals; ADAPTIVE SPARSE RECONSTRUCTIONS; IMAGE COMPLETION; FILLING-IN; INTERPOLATION; MODEL; REGULARIZATION; FIELDS; CURVE; COLOR; SHAPE;
D O I
10.1137/110823572
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Exemplar-based methods have proven their efficiency for the reconstruction of missing parts in a digital image. Texture as well as local geometry are often very well restored by such methods. Some applications, however, require the ability to reconstruct nonlocal geometric features, e. g., long edges. In order to do so, we propose to first compute a geometric sketch, which is then interpolated and used as a guide for the global reconstruction. In comparison with other related approaches, the originality of our work relies on the following points: (1) The geometric sketch computation is parameter-free and based on level lines, which provides a complete, reliable, and stable representation of the image. (2) The completion of the geometric sketch is fully automatic. It is done using a new-and interesting on its own-geometric inpainting approach that interpolates level lines with Euler spirals. Euler spirals are natural curves for shape completion and have been used already for edge completion and inpainting. It is the first time, however, that these curves are used for completing the whole level lines structure. (3) The general reconstruction is performed using a guided version of a classical exemplar-based method. However, we do not constrain the exemplar-based reconstruction to strictly follow the geometric guide. We actually use a new metric between blocks that consists of the sum of the classical L-2 metric between any two blocks of the general image plus an L-2 metric between the corresponding blocks in the completed geometric image. This is equivalent to a Lagrangian relaxation of a strictly guided reconstruction. We discuss in the paper the details of the method and some related mathematical issues, and we illustrate its efficiency on several examples.
引用
收藏
页码:1143 / 1179
页数:37
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