Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution sampling procedure for analysis and synthesis of texture images
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Fast texture synthesis using tree-structured vector quantization
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Image quilting for texture synthesis and transfer
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Texture Synthesis by Non-Parametric Sampling
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Graphcut textures: image and video synthesis using graph cuts
ACM SIGGRAPH 2003 Papers
Fragment-based image completion
ACM SIGGRAPH 2003 Papers
Texture Segmentation by Multiscale Aggregation of Filter Responses and Shape Elements
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Inference of Segmented Color and Texture Description by Tensor Voting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image completion with structure propagation
ACM SIGGRAPH 2005 Papers
Multi-resolution image inpainting
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Efficient Beltrami flow using a short time kernel
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
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Most patch based image completion algorithms fill in missing parts of images by copying patches from the known part of the image into the unknown part. The criterion for preferring one patch over another is the compatibility or consistency of the proposed patch with the nearby region that is known or already completed. In this paper we propose adding another dimension to this consistency criterion, namely, scale. Thus, the preferred patch is chosen by evaluating its consistency with respect to smoothed (less detailed) versions of the image, as well as its surroundings in the current version. Applied recursively, this approach results in a multi-scale framework that is shown to yield a dramatic improvement in the robustness of a good existing image completion algorithm.