Geometry-Driven Diffusion in Computer Vision

Preface. Foreword. 1. Linear Scale-Space I: Basic Theory T. Lindeberg, B.M. ter Haar Romeny. 2. Linear Scale-Space II: 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. Nordstroem. 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 Analysis: From Principles to Equations l. Alvarez, J.-M. Morel. 11. Differential Invariant Signatures and Flows in Computer Vision: 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.

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