Geometry-Driven Diffusion in Computer Vision

Preface. Foreword. 1. Linear Scale-Space Basic Theory; T. Lindeberg, B.M. ter Haar Romeny. 2. Linear Scale-Space Early Visual Operations; T. Lindeberg, B.M. ter Haar Romeny. 3. Anisotropic Diffusion; P. Perona, T. Shiota, J. Malik. 4. Vector-Valued Diffusion; R. Whitaker, G. Gerig. 5. Bayesian Rationale for the Variational Formulation; D. Mumford. 6. Variational Problems with a Free Discontinuity Set; A. Leaci, S. Solimini. 7. Minimization of Energy Functional with Curve-Represented Edges; N. Nordström. 8. Approximation, Computation, and Distortion in the Variational Formulation; T. Richardson, S. Mitter. 9. Coupled Geometry-Driven Diffusion Equations for Low-Level Vision; M. Proesmans, E. Pauwels, L. van Gool. 10. Morphological Approach to Multiscale From Principles to Equations; l. Alvarez, J.-M. Morel. 11. Differential Invariant Signatures and Flows in Computer a Symmetry Group Approach; P. Olver, G. Sapiro, A. Tannenbaum. 12. On Optimal Control Methods in Computer Vision and Image Processing; B. Kimia, A. Tannenbaum, S. Zucker. 13. Nonlinear Scale-Space; L. Florack, A. Salden, B. ter Haar Romeny, J. Koenderink, M. Viergever. 14. A Differential Geometric Approach to Anisotropic Diffusion; D. Eberly. 15. Numerical Analysis of Geometry-Driven Diffusion Equations; W. Niessen, B.M. ter Haar Romeny, M. Viergever. Bibliography. Index.