Image processing and analysis with graphs : theory and practice

Front Cover......Page 1
Dedication......Page 6
Preface......Page 8
The Editors......Page 14
Contributors......Page 16
Contents......Page 18
1. Graph theory concepts and definitions used in image processing and analysis......Page 26
2. Graph Cuts—Combinatorial Optimization in Vision......Page 50
3. Higher-Order Models in Computer Vision......Page 90
4. A Parametric Maximum Flow Approach for Discrete Total Variation Regularization......Page 118
5. Targeted Image Segmentation Using Graph Methods......Page 136
6. A Short Tour of Mathematical Morphology on Edge and Vertex Weighted Graphs......Page 166
7. Partial difference Equations on Graphs for Local and Nonlocal Image Processing......Page 200
8. Image Denoising with Nonlocal Spectral Graph Wavelets......Page 232
9. Image and Video Matting......Page 262
10. Optimal Simultaneous Multisurface and Multiobject Image Segmentation......Page 290
11 Hierarchical Graph Encodings......Page 330
12 Graph-Based Dimensionality Reduction......Page 376
13. Graph Edit Distance—Theory, Algorithms, and Applications......Page 408
14 The Role of Graphs in Matching Shapes and in Categorization......Page 448
15. 3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching......Page 466
16. Modeling Images with Undirected Graphical Models......Page 500
17. Tree-Walk Kernels for Computer Vision......Page 524