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Other titles in the Mathematics and Visualization series:
Image Processing Based on Partial Differential Equations: Proceedings of the International Conference on Pde-Based Image Processing and Related Invers (Mathematics and Visualization)by Xue-cheng Tai
Synopses & Reviews
This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. The topics covered in this book include: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems. The book is suitable for readers working with computer vision and visualization, image and signal processing, as well as medical imaging and numerical mathematics. The partial differential equations used for different problems discussed in this proceeding provide some rich research topics for people working with mathematical analysis and numerical simulations. This volume collects new developments in this field and points to the newest literature results. It is good resource for people working on related problems as well as for people who are new in this field.
This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems.
Table of Contents
From the contents Part I Digital Image Inpainting, Image Dejittering, and Optical Flow Estimation. Image Inpainting Using a TV-Stokes Equation -Xue-Cheng Tai, Stanley Osher, Randi Holm. Error Analysis for H1 Based Wavelet Interpolations - Tony F. Chan, Hao-Min Zhou, Tie Zhou. Image Dejittering Based on Slicing Moments - Sung Ha Kang, Jianhong (Jackie) Shen. CLG Method for Optical Flow Estimation Based on Gradient Constancy Assumption - Adam Rabcewicz.- Part II Denoising and Total Variation Methods. On Multigrids for Solving a Class of Improved Total Variation Based Staircasing Reduction Models - Joseph Savage, Ke Chen. A Method for Total Variation-based Reconstruction of Noisy and Blurred Images - Qianshun Chang, Weicheng Wang, Jing Xu. Minimization of an Edge-Preserving Regularization Functional by Conjugate Gradient Type Methods - Jian-Feng Cai, Raymond H. Chan, Benedetta Morini. A Newton-type Total Variation Diminishing Flow - Wolfgang Ring. Chromaticity Denoising using Solution to the Skorokhod Problem - Dariusz Borkowski. Improved 3D Reconstruction of Interphase Chromosomes Based on Nonlinear Diffusion Filtering - Jan Huben´y, Pavel Matula, Petr Matula, Michal Kozubek.- Part III Image Segmentation. Application of Non-Convex BV Regularization for Image Segmentation - Klaus Frick, Otmar Scherzer. Region-Based Variational Problems and Normal Alignment -Geometric Interpretation of Descent PDEs - Jan Erik Solem, Niels Chr. Overgaard. Fast PCLSM with Newton Updating Algorithm - Xue-Cheng Tai, Chang-Hui Yao.- Part IV Fast Numerical Methods.
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