Image Processing Based on Partial Differential Equations

Proceedings of the International Conference on PDE-Based Image Processing and Related Invers

By: Xue-Cheng Tai (Editor), Knut-Andreas Lie (Editor), Tony F. Chan (Editor)

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Hardcover | 1 December 2006

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452 Pages

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23.5 x 15.24 x 1.91

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The book contains twenty-two original scienti?c research articles that address the state-of-the-art in using partial di?erential equations for image and signal processing. The articles arose from presentations given at the inter- tional conference on PDE-Based Image Processing and Related Inverse Pr- lems, held at the Centre of Mathematics for Applications, University of Oslo, Norway, August 8-12, 2005. The purpose of the conference was to bring together international - searchers to present various aspects of new developments in using numerical techniques for partial di?erential equations to analyse and process digital - ages. Various aspects of new trends and techniques in this ?eld were discussed in the conference, covering the following topics: * Level set methods and applications * Total variation regularization and other nonlinear ?lters * Noise analysis and removal * Image inpainting * Image dejittering * Optical ?ow estimation * Image segmentation * Image registration * Analysis and processing of MR images and brain mapping * Image construction techniques * Level set methods for inverse problems Inverse problems for partial di?erential equations have large areas of app- cations. Although image analysis and PDE inverse problems seem to be - related at a ?rst glance, there are many techniques used in one of these two areas that are useful for the other. One goal of the conference was to highlight some of the recent e?orts in merging some of the techniques for these two research areas.

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Digital Image Inpainting, Image Dejittering, and Optical Flow Estimation
Image Inpainting Using a TV-Stokes Equation	p. 3
Error Analysis for H¹ Based Wavelet Interpolations	p. 23
Image Dejittering Based on Slicing Moments	p. 35
CLG Method for Optical Flow Estimation Based on Gradient Constancy Assumption	p. 57
Denoising and Total Variation Methods
On Multigrids for Solving a Class of Improved Total Variation Based Staircasing Reduction Models	p. 69
A Method for Total Variation-based Reconstruction of Noisy and Blurred Images	p. 95
Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods	p. 109
A Newton-type Total Variation Diminishing Flow	p. 123
Chromaticity Denoising using Solution to the Skorokhod Problem	p. 149
Improved 3D Reconstruction of Interphase Chromosomes Based on Nonlinear Diffusion Filtering	p. 163
Image Segmentation
Some Recent Developments in Variational Image Segmentation	p. 175
Application of Non-Convex BV Regularization for Image Segmentation	p. 211
Region-Based Variational Problems and Normal Alignment -Geometric Interpretation of Descent PDEs	p. 229
Fast PCLSM with Newton Updating Algorithm	p. 249
Fast Numerical Methods
Nonlinear Multilevel Schemes for Solving the Total Variation Image Minimization Problem	p. 265
Fast Implementation of Piecewise Constant Level Set Methods	p. 289
The Multigrid Image Transform	p. 309
Minimally Stochastic Schemes for Singular Diffusion Equations	p. 325
Image Registration
Total Variation Based Image Registration	p. 343
Variational Image Registration Allowing for Discontinuities in the Displacement Field	p. 363
Inverse Problems
Shape Reconstruction from Two-Phase Incompressible Flow Data using Level Sets	p. 381
Reservoir Description Using a Binary Level Set Approach with Additional Prior Information About the Reservoir Model	p. 403
Color Figures	p. 427
Table of Contents provided by Publisher. All Rights Reserved.

Image Processing Based on Partial Differential Equations

Proceedings of the International Conference on PDE-Based Image Processing and Related Invers

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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