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Mathematical Problems in Image Processing

Author: Gilles Aubert

Publisher: Springer Science & Business Media

Published: 2008-04-06

Total Pages: 303

ISBN-13: 0387217665

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Partial differential equations and variational methods were introduced into image processing about 15 years ago, and intensive research has been carried out since then. The main goal of this work is to present the variety of image analysis applications and the precise mathematics involved. It is intended for two audiences. The first is the mathematical community, to show the contribution of mathematics to this domain and to highlight some unresolved theoretical questions. The second is the computer vision community, to present a clear, self-contained, and global overview of the mathematics involved in image processing problems. The book is divided into five main parts. Chapter 1 is a detailed overview. Chapter 2 describes and illustrates most of the mathematical notions found throughout the work. Chapters 3 and 4 examine how PDEs and variational methods can be successfully applied in image restoration and segmentation processes. Chapter 5, which is more applied, describes some challenging computer vision problems, such as sequence analysis or classification. This book will be useful to researchers and graduate students in mathematics and computer vision.

Book Synopsis Mathematical Problems in Image Processing by : Gilles Aubert

Download or read book Mathematical Problems in Image Processing written by Gilles Aubert and published by Springer Science & Business Media. This book was released on 2008-04-06 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partial differential equations and variational methods were introduced into image processing about 15 years ago, and intensive research has been carried out since then. The main goal of this work is to present the variety of image analysis applications and the precise mathematics involved. It is intended for two audiences. The first is the mathematical community, to show the contribution of mathematics to this domain and to highlight some unresolved theoretical questions. The second is the computer vision community, to present a clear, self-contained, and global overview of the mathematics involved in image processing problems. The book is divided into five main parts. Chapter 1 is a detailed overview. Chapter 2 describes and illustrates most of the mathematical notions found throughout the work. Chapters 3 and 4 examine how PDEs and variational methods can be successfully applied in image restoration and segmentation processes. Chapter 5, which is more applied, describes some challenging computer vision problems, such as sequence analysis or classification. This book will be useful to researchers and graduate students in mathematics and computer vision.

Mathematical Image Processing

Author: Kristian Bredies

Publisher: Springer

Published: 2019-02-06

Total Pages: 473

ISBN-13: 3030014584

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This book addresses the mathematical aspects of modern image processing methods, with a special emphasis on the underlying ideas and concepts. It discusses a range of modern mathematical methods used to accomplish basic imaging tasks such as denoising, deblurring, enhancing, edge detection and inpainting. In addition to elementary methods like point operations, linear and morphological methods, and methods based on multiscale representations, the book also covers more recent methods based on partial differential equations and variational methods. Review of the German Edition: The overwhelming impression of the book is that of a very professional presentation of an appropriately developed and motivated textbook for a course like an introduction to fundamentals and modern theory of mathematical image processing. Additionally, it belongs to the bookcase of any office where someone is doing research/application in image processing. It has the virtues of a good and handy reference manual. (zbMATH, reviewer: Carl H. Rohwer, Stellenbosch)

Book Synopsis Mathematical Image Processing by : Kristian Bredies

Download or read book Mathematical Image Processing written by Kristian Bredies and published by Springer. This book was released on 2019-02-06 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the mathematical aspects of modern image processing methods, with a special emphasis on the underlying ideas and concepts. It discusses a range of modern mathematical methods used to accomplish basic imaging tasks such as denoising, deblurring, enhancing, edge detection and inpainting. In addition to elementary methods like point operations, linear and morphological methods, and methods based on multiscale representations, the book also covers more recent methods based on partial differential equations and variational methods. Review of the German Edition: The overwhelming impression of the book is that of a very professional presentation of an appropriately developed and motivated textbook for a course like an introduction to fundamentals and modern theory of mathematical image processing. Additionally, it belongs to the bookcase of any office where someone is doing research/application in image processing. It has the virtues of a good and handy reference manual. (zbMATH, reviewer: Carl H. Rohwer, Stellenbosch)

Mathematics in Image Processing

Author: Hong-Kai Zhao

Publisher: American Mathematical Soc.

Published: 2013-06-12

Total Pages: 258

ISBN-13: 0821898418

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The theme of the 2010 PCMI Summer School was Mathematics in Image Processing in a broad sense, including mathematical theory, analysis, computation algorithms and applications. In image processing, information needs to be processed, extracted and analyzed from visual content, such as photographs or videos. These demands include standard tasks such as compression and denoising, as well as high-level understanding and analysis, such as recognition and classification. Centered on the theme of mathematics in image processing, the summer school covered quite a wide spectrum of topics in this field. The summer school is particularly timely and exciting due to the very recent advances and developments in the mathematical theory and computational methods for sparse representation. This volume collects three self-contained lecture series. The topics are multi-resolution based wavelet frames and applications to image processing, sparse and redundant representation modeling of images and simulation of elasticity, biomechanics, and virtual surgery. Recent advances in image processing, compressed sensing and sparse representation are discussed.

Book Synopsis Mathematics in Image Processing by : Hong-Kai Zhao

Download or read book Mathematics in Image Processing written by Hong-Kai Zhao and published by American Mathematical Soc.. This book was released on 2013-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theme of the 2010 PCMI Summer School was Mathematics in Image Processing in a broad sense, including mathematical theory, analysis, computation algorithms and applications. In image processing, information needs to be processed, extracted and analyzed from visual content, such as photographs or videos. These demands include standard tasks such as compression and denoising, as well as high-level understanding and analysis, such as recognition and classification. Centered on the theme of mathematics in image processing, the summer school covered quite a wide spectrum of topics in this field. The summer school is particularly timely and exciting due to the very recent advances and developments in the mathematical theory and computational methods for sparse representation. This volume collects three self-contained lecture series. The topics are multi-resolution based wavelet frames and applications to image processing, sparse and redundant representation modeling of images and simulation of elasticity, biomechanics, and virtual surgery. Recent advances in image processing, compressed sensing and sparse representation are discussed.

Mathematical Methods in Image Processing and Inverse Problems

Author: Xue-Cheng Tai

Publisher: Springer Nature

Published: 2021-09-25

Total Pages: 226

ISBN-13: 9811627010

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This book contains eleven original and survey scientific research articles arose from presentations given by invited speakers at International Workshop on Image Processing and Inverse Problems, held in Beijing Computational Science Research Center, Beijing, China, April 21–24, 2018. The book was dedicated to Professor Raymond Chan on the occasion of his 60th birthday. The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.

Book Synopsis Mathematical Methods in Image Processing and Inverse Problems by : Xue-Cheng Tai

Download or read book Mathematical Methods in Image Processing and Inverse Problems written by Xue-Cheng Tai and published by Springer Nature. This book was released on 2021-09-25 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains eleven original and survey scientific research articles arose from presentations given by invited speakers at International Workshop on Image Processing and Inverse Problems, held in Beijing Computational Science Research Center, Beijing, China, April 21–24, 2018. The book was dedicated to Professor Raymond Chan on the occasion of his 60th birthday. The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.

Image Processing

Author: Jonathan M. Blackledge

Publisher:

Published: 1997

Total Pages: 548

ISBN-13:

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Digital image processing technology has developed markedly over the last ten years, and more and more information is being conveyed through its display and analysis. The way in which image data is stored and processed is fundamental to all aspects of information technology. Examples include remote sensing using digital satellites; making diagnoses using conventional X-ray computed tomography; and research into the behavior of the human brain using magnetic resonance imaging. This book consists of twenty-one papers that collectively cover a broad range of image processing problems and the way in which their solutions are used in different areas of science and technology. The papers present details of the ways computers of varying processing power can be programmed to store images efficiently, resolve features and patterns that are either time consuming or impossible for humans to interpret, and develop machines that can "see" like humans. They also discuss a wide range of applications, including the use of lasers for studying dynamic behavior of mechanical components, and fractal geometry for recognizing patterns. The book will be useful to any engineer, scientist, and technologist interested in current research issues in image processing.

Book Synopsis Image Processing by : Jonathan M. Blackledge

Download or read book Image Processing written by Jonathan M. Blackledge and published by . This book was released on 1997 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital image processing technology has developed markedly over the last ten years, and more and more information is being conveyed through its display and analysis. The way in which image data is stored and processed is fundamental to all aspects of information technology. Examples include remote sensing using digital satellites; making diagnoses using conventional X-ray computed tomography; and research into the behavior of the human brain using magnetic resonance imaging. This book consists of twenty-one papers that collectively cover a broad range of image processing problems and the way in which their solutions are used in different areas of science and technology. The papers present details of the ways computers of varying processing power can be programmed to store images efficiently, resolve features and patterns that are either time consuming or impossible for humans to interpret, and develop machines that can "see" like humans. They also discuss a wide range of applications, including the use of lasers for studying dynamic behavior of mechanical components, and fractal geometry for recognizing patterns. The book will be useful to any engineer, scientist, and technologist interested in current research issues in image processing.

Mathematical Morphology and Its Applications to Image Processing

Author: Jean Serra

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 391

ISBN-13: 9401110409

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Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, etc. MM is not only a theory, but also a powerful image analysis technique. The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.

Book Synopsis Mathematical Morphology and Its Applications to Image Processing by : Jean Serra

Download or read book Mathematical Morphology and Its Applications to Image Processing written by Jean Serra and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical morphology (MM) is a theory for the analysis of spatial structures. It is called morphology since it aims at analysing the shape and form of objects, and it is mathematical in the sense that the analysis is based on set theory, topology, lattice algebra, random functions, etc. MM is not only a theory, but also a powerful image analysis technique. The purpose of the present book is to provide the image analysis community with a snapshot of current theoretical and applied developments of MM. The book consists of forty-five contributions classified by subject. It demonstrates a wide range of topics suited to the morphological approach.

Variational Methods in Image Processing

Author: Luminita A. Vese

Publisher: CRC Press

Published: 2015-11-18

Total Pages: 416

ISBN-13: 1439849749

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Variational Methods in Image Processing presents the principles, techniques, and applications of variational image processing. The text focuses on variational models, their corresponding Euler-Lagrange equations, and numerical implementations for image processing. It balances traditional computational models with more modern techniques that solve t

Book Synopsis Variational Methods in Image Processing by : Luminita A. Vese

Download or read book Variational Methods in Image Processing written by Luminita A. Vese and published by CRC Press. This book was released on 2015-11-18 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Variational Methods in Image Processing presents the principles, techniques, and applications of variational image processing. The text focuses on variational models, their corresponding Euler-Lagrange equations, and numerical implementations for image processing. It balances traditional computational models with more modern techniques that solve t

Image Processing Based on Partial Differential Equations

Author: Xue-Cheng Tai

Publisher: Springer Science & Business Media

Published: 2006-11-22

Total Pages: 440

ISBN-13: 3540332677

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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.

Book Synopsis Image Processing Based on Partial Differential Equations by : Xue-Cheng Tai

Download or read book Image Processing Based on Partial Differential Equations written by Xue-Cheng Tai and published by Springer Science & Business Media. This book was released on 2006-11-22 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Image Processing and Analysis

Author: Tony F. Chan

Publisher: SIAM

Published: 2005-09-01

Total Pages: 414

ISBN-13: 089871589X

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This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.

Book Synopsis Image Processing and Analysis by : Tony F. Chan

Download or read book Image Processing and Analysis written by Tony F. Chan and published by SIAM. This book was released on 2005-09-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.

Statistical Image Processing and Multidimensional Modeling

Author: Paul Fieguth

Publisher: Springer Science & Business Media

Published: 2010-10-17

Total Pages: 465

ISBN-13: 1441972943

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Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.

Book Synopsis Statistical Image Processing and Multidimensional Modeling by : Paul Fieguth

Download or read book Statistical Image Processing and Multidimensional Modeling written by Paul Fieguth and published by Springer Science & Business Media. This book was released on 2010-10-17 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.