[PDF] Statistical Image Processing And Multidimensional Modeling Modelling Of Random Fields - eBooks Review

Statistical Image Processing And Multidimensional Modeling Modelling Of Random Fields


Statistical Image Processing And Multidimensional Modeling Modelling Of Random Fields
DOWNLOAD

Download Statistical Image Processing And Multidimensional Modeling Modelling Of Random Fields PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Statistical Image Processing And Multidimensional Modeling Modelling Of Random Fields book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page



Statistical Image Processing And Multidimensional Modeling


Statistical Image Processing And Multidimensional Modeling
DOWNLOAD
Author : Paul Fieguth
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-17

Statistical Image Processing And Multidimensional Modeling written by Paul Fieguth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-17 with Mathematics categories.


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.



Multidimensional Signal And Color Image Processing Using Lattices


Multidimensional Signal And Color Image Processing Using Lattices
DOWNLOAD
Author : Eric Dubois
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-19

Multidimensional Signal And Color Image Processing Using Lattices written by Eric Dubois and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-19 with Technology & Engineering categories.


An Innovative Approach to Multidimensional Signals and Systems Theory for Image and Video Processing In this volume, Eric Dubois further develops the theory of multi-D signal processing wherein input and output are vector-value signals. With this framework, he introduces the reader to crucial concepts in signal processing such as continuous- and discrete-domain signals and systems, discrete-domain periodic signals, sampling and reconstruction, light and color, random field models, image representation and more. While most treatments use normalized representations for non-rectangular sampling, this approach obscures much of the geometrical and scale information of the signal. In contrast, Dr. Dubois uses actual units of space-time and frequency. Basis-independent representations appear as much as possible, and the basis is introduced where needed to perform calculations or implementations. Thus, lattice theory is developed from the beginning and rectangular sampling is treated as a special case. This is especially significant in the treatment of color and color image processing and for discrete transform representations based on symmetry groups, including fast computational algorithms. Other features include: An entire chapter on lattices, giving the reader a thorough grounding in the use of lattices in signal processing Extensive treatment of lattices as used to describe discrete-domain signals and signal periodicities Chapters on sampling and reconstruction, random field models, symmetry invariant signals and systems and multidimensional Fourier transformation properties Supplemented throughout with MATLAB examples and accompanying downloadable source code Graduate and doctoral students as well as senior undergraduates and professionals working in signal processing or video/image processing and imaging will appreciate this fresh approach to multidimensional signals and systems theory, both as a thorough introduction to the subject and as inspiration for future research.



Invariant Random Fields On Spaces With A Group Action


Invariant Random Fields On Spaces With A Group Action
DOWNLOAD
Author : Anatoliy Malyarenko
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-26

Invariant Random Fields On Spaces With A Group Action written by Anatoliy Malyarenko and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-26 with Mathematics categories.


The author describes the current state of the art in the theory of invariant random fields. This theory is based on several different areas of mathematics, including probability theory, differential geometry, harmonic analysis, and special functions. The present volume unifies many results scattered throughout the mathematical, physical, and engineering literature, as well as it introduces new results from this area first proved by the author. The book also presents many practical applications, in particular in such highly interesting areas as approximation theory, cosmology and earthquake engineering. It is intended for researchers and specialists working in the fields of stochastic processes, statistics, functional analysis, astronomy, and engineering.



Computer Vision In Control Systems 3


Computer Vision In Control Systems 3
DOWNLOAD
Author : Margarita N. Favorskaya
language : en
Publisher: Springer
Release Date : 2017-10-25

Computer Vision In Control Systems 3 written by Margarita N. Favorskaya and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-25 with Technology & Engineering categories.


The research book is a continuation of the authors’ previous works, which are focused on recent advances in computer vision methodologies and technical solutions using conventional and intelligent paradigms. The book gathers selected contributions addressing aerial and satellite image processing and related fields. Topics covered include novel tensor and wave models, a new comparative morphology scheme, warping compensation in video stabilization, image deblurring based on physical processes of blur impacts, and a rapid and robust core structural verification algorithm for feature extraction in images and videos, among others. All chapters focus on practical implementations. Given the tremendous interest among researchers in the development and applications of computer vision paradigms in the field of business, engineering, medicine, security and aviation, this book offers a timely guide.



Time Series Analysis Methods And Applications


Time Series Analysis Methods And Applications
DOWNLOAD
Author :
language : en
Publisher: Elsevier
Release Date : 2012-05-18

Time Series Analysis Methods And Applications written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-18 with Mathematics categories.


The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. - Comprehensively presents the various aspects of statistical methodology - Discusses a wide variety of diverse applications and recent developments - Contributors are internationally renowened experts in their respective areas



Research In Progress


Research In Progress
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1983

Research In Progress written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Military research categories.




Research In Progress


Research In Progress
DOWNLOAD
Author : United States. Army Research Office
language : en
Publisher:
Release Date : 1984

Research In Progress written by United States. Army Research Office and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Military research categories.


Vols. for 1977- consist of two parts: Chemistry, biological sciences, engineering sciences, metallurgy and materials science (issued in the spring); and Physics, electronics, mathematics, geosciences (issued in the fall).



Computer Vision In Advanced Control Systems 5


Computer Vision In Advanced Control Systems 5
DOWNLOAD
Author : Margarita N. Favorskaya
language : en
Publisher: Springer Nature
Release Date : 2019-12-07

Computer Vision In Advanced Control Systems 5 written by Margarita N. Favorskaya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-07 with Technology & Engineering categories.


This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.



Scientific And Technical Aerospace Reports


Scientific And Technical Aerospace Reports
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 1995

Scientific And Technical Aerospace Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Aeronautics categories.




Convolutional Fractional Stochastic Fields And Their Deep Learning


Convolutional Fractional Stochastic Fields And Their Deep Learning
DOWNLOAD
Author : Abdourrahmane M. Atto
language : en
Publisher: ISTE Group
Release Date : 2023-02-01

Convolutional Fractional Stochastic Fields And Their Deep Learning written by Abdourrahmane M. Atto and has been published by ISTE Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Mathematics categories.


In a stochastic environment where reality is described through samples or examples, artificial intelligence learns by penalizing weighted differential and/or integral viewpoints. The convolutional neural framework is relevant to encompass the mathematical operations performed by such an artificial intelligence. Conversely, mathematical compositions alternating convolutions and non linear operators are powerful tools for generating complex artificial realities. This book proposes a stochastic integral perspective of deep machine learning in artificial intelligence. The organization of the book is as follows. Chapter 1 introduces the basics of stochastic reasoning and the most useful properties of stochastic processes. Chapters 2 and 3 derive stochastic convoluted models for the construction, analysis and simulation of fractionally integrated fields. Chapter 4 highlights how some deep artificial neurons can disentangle the very long-range stochastic dependencies, when these neurons are parameterized to integrate spectral responses.