Browse > Article

A New Image Completion Method Using Hierarchical Priority Belief Propagation Algorithm  

Kim, Moo-Sung (Department of Computer Science, Catholic University of Korea)
Kang, Hang-Bong (Department of Computer Science, Catholic University of Korea)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.44, no.5, 2007 , pp. 54-63 More about this Journal
Abstract
The purpose of this study is to present a new energy minimization method for image completion with hierarchical approach. The goal of image completion is to fill in missing part in a possibly large region of an image so that a visually plausible outcome is obtained. An exemplar-based Markov Random Field Modeling(MRF) is proposed in this paper. This model can deal with following problems; detection of global features, flexibility on environmental changes, reduction of computational cost, and generic extension to other related domains such as image inpainting. We use the Priority Belief Propagation(Priority-BP) which is a kind of Belief propagation(BP) algorithms for the optimization of MRF. We propose the hierarchical Priority-BP that reduces the number of nodes in MRF and to apply hierarchical propagation of messages for image completion. We show that our approach which uses hierarchical Priority-BP algorithm in image completion works well on a number of examples.
Keywords
Image Completion; Belief Propagation; Priority Belief Propagation; MRF; Hierarchical Model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 V. Kwatra, I. Essa, A. Bobic, and N. Kwatra, 'Texture optimization for example-based synthesis,' in SIGGRAPH, 2005
2 A, Criminisi, P. Perez, and K. Toyam,. 'Object removal by exemplar-based inpainting,' in SIGGRAPH, 2000
3 Chris Bishop. 'Pattern Recognition and Machine Learning,' Springer. 359-422, 2006
4 Y. Wexler, E. Shechtman, and M. Irani, 'Space-time video completion,' in CVPR, pages 120-127, 2004
5 A. A. Efros and T. K. Leung, 'Texture synthesis by non-parametric sampling,' in ICCV, 1999
6 J. Yedida, W. T. Freeman, and Y. Weiss, 'Understanding belief propagation and its generalizations,' International Joint Conference on Artificial Intelligence (IJCAI), 2001
7 P. F. Felzenszwalb and D. P. Huttenlocher, 'Efficient belief propagation for early vision,' in CVPR, 2004
8 J. Sun, L. Yuan, J. Jia, and H.-Y. Shum, 'Image completion with structure propagation,' in SIGGRAPH, 2005
9 I. Drori, D. Cohen-Or, and H. Yeshurn, 'Fragment-based image completion,' in SIGGRAPH, 2003
10 N. Komodakis and G. Tziritas, 'Image Completion Using Global Optimization,' in CVPR, 2006
11 V. Kwatra and et al. 'Graphcut textures: Image and video synthesis using graph cuts,' in SIGGRAPH, 2003
12 D. J. Heeger, and J. R. Bergen, 'Pyramid-based texture analysis synthesis,' in Proceedings of SIGGRAPH, 1995
13 J. Pearl, 'Probabilistic Reasoning in Intelligent Systems : Networks of Plausible inference,' Morgan Kaufmann Publishers Inc., 1988