Statistical Image Processing and Multidimensional Modeling: Modelling of random fields

Statistical Image Processing and Multidimensional Modeling: Modelling of random fields PDF Author: Paul Fieguth
Publisher:
ISBN: 9781416427056
Category : Image processing
Languages : en
Pages : 454

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Book Description

Statistical Image Processing and Multidimensional Modeling: Modelling of random fields

Statistical Image Processing and Multidimensional Modeling: Modelling of random fields PDF Author: Paul Fieguth
Publisher:
ISBN: 9781416427056
Category : Image processing
Languages : en
Pages : 454

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Book Description


Statistical Image Processing and Multidimensional Modeling

Statistical Image Processing and Multidimensional Modeling PDF Author: Paul Fieguth
Publisher: Springer Science & Business Media
ISBN: 1441972943
Category : Mathematics
Languages : en
Pages : 465

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Book Description
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.

Computational and Statistical Methods in Intelligent Systems

Computational and Statistical Methods in Intelligent Systems PDF Author: Radek Silhavy
Publisher: Springer
ISBN: 303000211X
Category : Technology & Engineering
Languages : en
Pages : 399

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Book Description
This book presents real-world problems and pioneering research in computational statistics, mathematical modeling, artificial intelligence and software engineering in the context of intelligent systems. It gathers the peer-reviewed proceedings of the 2nd Computational Methods in Systems and Software 2018 (CoMeSySo 2018), a conference that broke down traditional barriers by being held online. The goal of the event was to provide an international forum for discussing the latest high-quality research results.

Frontiers in Statistical Quality Control 13

Frontiers in Statistical Quality Control 13 PDF Author: Sven Knoth
Publisher: Springer Nature
ISBN: 3030678563
Category : Mathematics
Languages : en
Pages : 410

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Book Description
This contributed book focuses on major aspects of statistical quality control, shares insights into important new developments in the field, and adapts established statistical quality control methods for use in e.g. big data, network analysis and medical applications. The content is divided into two parts, the first of which mainly addresses statistical process control, also known as statistical process monitoring. In turn, the second part explores selected topics in statistical quality control, including measurement uncertainty analysis and data quality. The peer-reviewed contributions gathered here were originally presented at the 13th International Workshop on Intelligent Statistical Quality Control, ISQC 2019, held in Hong Kong on August 12-14, 2019. Taken together, they bridge the gap between theory and practice, making the book of interest to both practitioners and researchers in the field of statistical quality control.

Computer Vision in Control Systems-1

Computer Vision in Control Systems-1 PDF Author: Margarita N. Favorskaya
Publisher: Springer
ISBN: 3319106538
Category : Technology & Engineering
Languages : en
Pages : 385

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Book Description
This book is focused on the recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The Contributions include: · Morphological Image Analysis for Computer Vision Applications. · Methods for Detecting of Structural Changes in Computer Vision Systems. · Hierarchical Adaptive KL-based Transform: Algorithms and Applications. · Automatic Estimation for Parameters of Image Projective Transforms Based on Object-invariant Cores. · A Way of Energy Analysis for Image and Video Sequence Processing. · Optimal Measurement of Visual Motion Across Spatial and Temporal Scales. · Scene Analysis Using Morphological Mathematics and Fuzzy Logic. · Digital Video Stabilization in Static and Dynamic Scenes. · Implementation of Hadamard Matrices for Image Processing. · A Generalized Criterion of Efficiency for Telecommunication Systems. The book is directed to PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies.

Image Analysis and Recognition

Image Analysis and Recognition PDF Author: Mohamed Kamel
Publisher: Springer Science & Business Media
ISBN: 3642215920
Category : Computers
Languages : en
Pages : 467

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Book Description
The two-volume set LNCS 6753/6754 constitutes the refereed proceedings of the 8th International Conference on Image and Recognition, ICIAR 2011, held in Burnaby, Canada, in June 2011. The 84 revised full papers presented were carefully reviewed and selected from 147 submissions. The papers are organized in topical sections on image and video processing; feature extraction and pattern recognition; computer vision; color, texture, motion and shape; tracking; biomedical image analysis; biometrics; face recognition; image coding, compression and encryption; and applications.

Mathematical Modeling and Simulation of Systems

Mathematical Modeling and Simulation of Systems PDF Author: Serhiy Shkarlet
Publisher: Springer Nature
ISBN: 3030899020
Category : Technology & Engineering
Languages : en
Pages : 489

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Book Description
This book contains works on mathematical and simulation modeling of processes in various domains: ecology and geographic information systems, IT, industry, and project management. The development of complex multicomponent systems requires an increase in accuracy, efficiency, and adequacy while reducing the cost of their creation. The studies presented in the book are useful to specialists who involved in the development of real events models-analog, management and decision-making models, production models, and software products. Scientists can get acquainted with the latest research in various decisions proposed by leading scholars and identify promising directions for solving complex scientific and practical problems. The chapters of this book contain the contributions presented on the 16th International Scientific-practical Conference, MODS, June 28–July 01, 2021, Chernihiv, Ukraine.

Wavelets in Functional Data Analysis

Wavelets in Functional Data Analysis PDF Author: Pedro A. Morettin
Publisher: Springer
ISBN: 3319596233
Category : Mathematics
Languages : en
Pages : 112

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Book Description
Wavelet-based procedures are key in many areas of statistics, applied mathematics, engineering, and science. This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data. Starting with the Haar wavelet, the authors explore myriad families of wavelets and how they can be used. High-dimensional data visualization (using Andrews' plots), wavelet shrinkage (a simple, yet powerful, procedure for nonparametric models) and a selection of estimation and testing techniques (including a discussion on Stein’s Paradox) make this a highly valuable resource for graduate students and experienced researchers alike.

Emerging Topics in Computer Vision and Its Applications

Emerging Topics in Computer Vision and Its Applications PDF Author: C. H. Chen
Publisher: World Scientific
ISBN: 9814343005
Category : Computers
Languages : en
Pages : 508

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Book Description
This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.

An Introduction to Pattern Recognition and Machine Learning

An Introduction to Pattern Recognition and Machine Learning PDF Author: Paul Fieguth
Publisher: Springer Nature
ISBN: 3030959953
Category : Technology & Engineering
Languages : en
Pages : 481

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Book Description
The domains of Pattern Recognition and Machine Learning have experienced exceptional interest and growth, however the overwhelming number of methods and applications can make the fields seem bewildering. This text offers an accessible and conceptually rich introduction, a solid mathematical development emphasizing simplicity and intuition. Students beginning to explore pattern recognition do not need a suite of mathematically advanced methods or complicated computational libraries to understand and appreciate pattern recognition; rather the fundamental concepts and insights, eminently teachable at the undergraduate level, motivate this text. This book provides methods of analysis that the reader can realistically undertake on their own, supported by real-world examples, case-studies, and worked numerical / computational studies.