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)
Download or read book Mathematical Foundations of Imaging Tomography and Wavefield Inversion written by Anthony J. Devaney and published by Cambridge University Press. This book was released on 2012-06-21 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic presentation of the foundations of imaging and wavefield inversion that bridges the gap between mathematics and physics.
Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.
Download or read book Mathematical and Statistical Methods for Multistatic Imaging written by Habib Ammari and published by Springer. This book was released on 2013-11-29 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent mathematical, numerical, and statistical approaches for multistatic imaging of targets with waves at single or multiple frequencies. The waves can be acoustic, elastic or electromagnetic. They are generated by point sources on a transmitter array and measured on a receiver array. An important problem in multistatic imaging is to quantify and understand the trade-offs between data size, computational complexity, signal-to-noise ratio, and resolution. Another fundamental problem is to have a shape representation well suited to solving target imaging problems from multistatic data. In this book the trade-off between resolution and stability when the data are noisy is addressed. Efficient imaging algorithms are provided and their resolution and stability with respect to noise in the measurements analyzed. It also shows that high-order polarization tensors provide an accurate representation of the target. Moreover, a dictionary-matching technique based on new invariants for the generalized polarization tensors is introduced. Matlab codes for the main algorithms described in this book are provided. Numerical illustrations using these codes in order to highlight the performance and show the limitations of numerical approaches for multistatic imaging are presented.
Download or read book Magnetic Resonance Imaging written by Walter Johannes Schempp and published by Wiley-Liss. This book was released on 1998-09-30 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: MAGNETIC RESONANCE IMAGING Mathematical Foundations and Applications By Walter J. Schempp As magnetic resonance imaging (MRI) continues to transform medical diagnostics and the study of the brain, the necessity for a more precise description of this important clinical tool is increasingly evident. A mathematical understanding of MRI and the related imaging modalities of functional MRI and NMR spectroscopy can greatly improve many scientific and medical endeavors, from the quality of scans in the tomographic slices and their semantic interpretations to minimally invasive neurosurgery and research in cognitive neuroscience. Magnetic Resonance Imaging advances a coherent mathematical theory of MRI and presents for the first time a real-world application of non-commutative Fourier analysis. Emphasizing the interdisciplinary nature of clinical MRI, this book offers an intriguing look at the geometric principles underlying the quantum phenomena of biomedical research. Author Walter J. Schempp, widely respected among mathematicians and neuro-network scientists alike, includes in this lucid, readable text: * The historical and phenomenological aspects of NMR spectroscopy and clinical MRI * A mathematical approach to the structure-function problem in clinical MRI * Detailed descriptions of applications to medical diagnostics * Photographs illustrating the superior contrast and spatial resolution achieved by MRI * An extensive list of references. Magnetic Resonance Imaging introduces clinical and mathematical concepts gradually and deliberately, making the complex procedure of MRI accessible to professionals in all areas of neuroscience and neurology, as well as those in mathematics, engineering, radiology, and physics.
Download or read book Mathematical Methods in Image Reconstruction written by Frank Natterer and published by SIAM. This book was released on 2001-01-01 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a superior understanding of the mathematical principles behind imaging.
Download or read book Variational Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2008-09-26 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Many numerical examples accompany the theory throughout the text. It is geared towards graduate students and researchers in applied mathematics. Researchers in the area of imaging science will also find this book appealing. It can serve as a main text in courses in image processing or as a supplemental text for courses on regularization and inverse problems at the graduate level.
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.
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.
Download or read book The Mathematics of Medical Imaging written by Timothy G. Feeman and published by Springer Science & Business Media. This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging is a major part of twenty-first century health care. This introduction explores the mathematical aspects of imaging in medicine to explain approximation methods in addition to computer implementation of inversion algorithms.
Download or read book Statistical and Computational Methods in Brain Image Analysis written by Moo K. Chung and published by CRC Press. This book was released on 2013-07-23 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.
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
Download or read book Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging written by Ke Chen and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Morphology and Its Applications to Image and Signal Processing written by Petros Maragos and published by Springer Science & Business Media. This book was released on 1996-05-31 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications
Download or read book Digital Image Processing written by J M Blackledge and published by Elsevier. This book was released on 2005-11-30 with total page 826 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. This book relates the methods of processing and interpreting digital images to the ‘physics’ of imaging systems. Case studies reinforce the methods discussed, with examples of current research themes. Provides mathematical methods required to describe images, image formation and different imaging systems Outlines the principle techniques used for processing digital images Relates the methods of processing and interpreting digital images to the ‘physics’ of imaging systems
Download or read book Mathematical Nonlinear Image Processing written by Edward R. Dougherty and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Nonlinear Image Processing deals with a fast growing research area. The development of the subject springs from two factors: (1) the great expansion of nonlinear methods applied to problems in imaging and vision, and (2) the degree to which nonlinear approaches are both using and fostering new developments in diverse areas of mathematics. Mathematical Nonlinear Image Processing will be of interest to people working in the areas of applied mathematics as well as researchers in computer vision. Mathematical Nonlinear Image Processing is an edited volume of original research. It has also been published as a special issue of the Journal of Mathematical Imaging and Vision. (Volume 2, Issue 2/3).
Download or read book Lesson Imaging in Math and Science written by Michelle Stephan and published by ASCD. This book was released on 2016-10-26 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: From respected voices in STEM education comes an innovative lesson planning approach to help turn students into problem solvers: lesson imaging.
