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Author : Seetharaman K.
Publisher :
Page : 144 pages
File Size : 15,29 MB
Release : 2014-04
Category :
ISBN : 9783659532153
Author : Chee Sun Won
Publisher : Springer Science & Business Media
Page : 176 pages
File Size : 22,19 MB
Release : 2013-11-27
Category : Computers
ISBN : 1441988572
Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.
Author : Jamshid Dehmeshki
Publisher :
Page : pages
File Size : 16,15 MB
Release : 1997
Category :
ISBN :
Author : Ayman El-Baz
Publisher : CRC Press
Page : 299 pages
File Size : 50,82 MB
Release : 2015-11-18
Category : Medical
ISBN : 1466599081
Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis.Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obt
Author : Charles A. Bouman
Publisher : SIAM
Page : 350 pages
File Size : 34,40 MB
Release : 2022-07-06
Category : Mathematics
ISBN : 1611977134
Collecting a set of classical and emerging methods previously unavailable in a single resource, Foundations of Computational Imaging: A Model-Based Approach is the first book to define a common foundation for the mathematical and statistical methods used in computational imaging. The book brings together a blend of research with applications in a variety of disciplines, including applied math, physics, chemistry, optics, and signal processing, to address a collection of problems that can benefit from a common set of methods. Readers will find basic techniques of model-based image processing, a comprehensive treatment of Bayesian and regularized image reconstruction methods, and an integrated treatment of advanced reconstruction techniques, such as majorization, constrained optimization, alternating direction method of multipliers (ADMM), and Plug-and-Play methods for model integration. Foundations of Computational Imaging can be used in courses on model-based or computational imaging, advanced numerical analysis, data science, numerical optimization, and approximation theory. It will also prove useful to researchers or practitioners in medical, scientific, commercial, and industrial imaging.
Author : Tony F. Chan
Publisher : SIAM
Page : 414 pages
File Size : 27,21 MB
Release : 2005-09-01
Category : Computers
ISBN : 089871589X
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.
Author : Xavier Descombes
Publisher : John Wiley & Sons
Page : 215 pages
File Size : 14,60 MB
Release : 2013-05-06
Category : Technology & Engineering
ISBN : 1118601130
This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
Author : Aly A. Farag
Publisher :
Page : 344 pages
File Size : 20,34 MB
Release : 1990
Category : Algorithms
ISBN :
A computational study was conducted on images having various types of texture images. The issues of parameter estimation, neighborhood selection, and model orders were examined. It is concluded that the MAP approach for region segmentation generally works well on images having a large content of microtextures which can be properly modeled by both AR and GMAF models. On the texture images, second order AR and GMRF models were shown to be adequate."
Author : Tony F. Chan
Publisher : SIAM
Page : 421 pages
File Size : 46,18 MB
Release : 2005-01-01
Category : Computers
ISBN : 9780898717877
At no other time in human history have the influence and impact of image processing on modern society, science, and technology been so explosive. Image processing has become a critical component in contemporary science and technology and has many important applications. This book develops the mathematical foundation of modern image processing and low-level computer vision, and presents a general framework from the analysis of image structures and patterns to their processing. The core mathematical and computational ingredients of several important image processing tasks are investigated. The book bridges contemporary mathematics with state-of-the-art methodologies in modern image processing while organizing the vast contemporary literature into a coherent and logical structure.
Author : Piero Barone
Publisher : Springer Science & Business Media
Page : 266 pages
File Size : 14,1 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 1461229200
This volume comprises a collection of papers by world- renowned experts on image analysis. The papers range from survey articles to research papers, and from theoretical topics such as simulated annealing through to applied image reconstruction. It covers applications as diverse as biomedicine, astronomy, and geophysics. As a result, any researcher working on image analysis will find this book provides an up-to-date overview of the field and in addition, the extensive bibliographies will make this a useful reference.