Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
CAD-CG '05 Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics
Space-Time Completion of Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
PatchMatch: a randomized correspondence algorithm for structural image editing
ACM SIGGRAPH 2009 papers
Image Repairing: robust image synthesis by adaptive ND tensor voting
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning
IEEE Transactions on Image Processing
Automatic crack detection in heritage site images for image inpainting
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Color-Aware regularization for gradient domain image manipulation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
SVD based automatic detection of target regions for image inpainting
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
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A novel inpainting method based on probabilistic structure estimation has been developed. The method consists of two steps. First, an initial image, which captures rough structure and colors in the missing region, is estimated. This image is generated by probabilistically interpolating the gradient inside the missing region, and then by flooding the colors on the boundary into the missing region using Markov Random Field. Second, by locally replacing the missing region with local patches similar to both the adjacent patches and the initial image, the inpainted image is synthesized. Since the patch replacement process is guided by the initial image, the inpainted image is guaranteed to preserve the underlying structure. This also enables patches to be replaced in a greedy manner, i.e. without optimization. Experiments show the proposed method outperforms previous methods in terms of both subjective image quality and computational speed.