Some Statistical Methods Of Image Processing And Reconstruction

DOWNLOAD

Download Some Statistical Methods Of Image Processing And Reconstruction PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Some Statistical Methods Of Image Processing And Reconstruction 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

Some Statistical Methods Of Image Processing And Reconstruction

DOWNLOAD
Author : Stavros Kariolis
language : en
Publisher:
Release Date : 1979

Some Statistical Methods Of Image Processing And Reconstruction written by Stavros Kariolis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Image processing categories.

Statistical Methods And Models For Video Based Tracking Modeling And Recognition

DOWNLOAD
Author : Rama Chellappa
language : en
Publisher: Now Publishers Inc
Release Date : 2010

Statistical Methods And Models For Video Based Tracking Modeling And Recognition written by Rama Chellappa and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.

Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. In this paper, we highlight the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.

Minimax Theory Of Image Reconstruction

DOWNLOAD
Author : A.P. Korostelev
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Minimax Theory Of Image Reconstruction written by A.P. Korostelev 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 2012-12-06 with Mathematics categories.

There exists a large variety of image reconstruction methods proposed by different authors (see e. g. Pratt (1978), Rosenfeld and Kak (1982), Marr (1982)). Selection of an appropriate method for a specific problem in image analysis has been always considered as an art. How to find the image reconstruction method which is optimal in some sense? In this book we give an answer to this question using the asymptotic minimax approach in the spirit of Ibragimov and Khasminskii (1980a,b, 1981, 1982), Bretagnolle and Huber (1979), Stone (1980, 1982). We assume that the image belongs to a certain functional class and we find the image estimators that achieve the best order of accuracy for the worst images in the class. This concept of optimality is rather rough since only the order of accuracy is optimized. However, it is useful for comparing various image reconstruction methods. For example, we show that some popular methods such as simple linewise processing and linear estimation are not optimal for images with sharp edges. Note that discontinuity of images is an important specific feature appearing in most practical situations where one has to distinguish between the "image domain" and the "background" . The approach of this book is based on generalization of nonparametric regression and nonparametric change-point techniques. We discuss these two basic problems in Chapter 1. Chapter 2 is devoted to minimax lower bounds for arbitrary estimators in general statistical models.

Stochastic Models Statistical Methods And Algorithms In Image Analysis

DOWNLOAD
Author : Piero Barone
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Stochastic Models Statistical Methods And Algorithms In Image Analysis written by Piero Barone 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 2012-12-06 with Mathematics categories.

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.

Spatial Statistics And Digital Image Analysis

DOWNLOAD
Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 1991-02-01

Spatial Statistics And Digital Image Analysis written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-02-01 with Mathematics categories.

Spatial statistics is one of the most rapidly growing areas of statistics, rife with fascinating research opportunities. Yet many statisticians are unaware of those opportunities, and most students in the United States are never exposed to any course work in spatial statistics. Written to be accessible to the nonspecialist, this volume surveys the applications of spatial statistics to a wide range of areas, including image analysis, geosciences, physical chemistry, and ecology. The book describes the contributions of the mathematical sciences, summarizes the current state of knowledge, and identifies directions for research.

Stochastic Models Statistical Methods And Algorithms In Image Analysis

DOWNLOAD
Author : Piero Barone
language : en
Publisher: Springer
Release Date : 1992-06-24

Stochastic Models Statistical Methods And Algorithms In Image Analysis written by Piero Barone and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-24 with Mathematics categories.

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.

Stochastic Models Statistical Methods And Algorithms In Image Analysis

DOWNLOAD
Author : Piero Barone
language : en
Publisher:
Release Date : 1992-06-24

Stochastic Models Statistical Methods And Algorithms In Image Analysis written by Piero Barone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-24 with Algorithms categories.

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.

Statistical Image Processing Techniques For Noisy Images

DOWNLOAD
Author : Phillipe Réfrégier
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-22

Statistical Image Processing Techniques For Noisy Images written by Phillipe Réfrégier 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 2013-11-22 with Computers categories.

Statistical Processing Techniques for Noisy Images presents a statistical framework to design algorithms for target detection, tracking, segmentation and classification (identification). Its main goal is to provide the reader with efficient tools for developing algorithms that solve his/her own image processing applications. In particular, such topics as hypothesis test-based detection, fast active contour segmentation and algorithm design for non-conventional imaging systems are comprehensively treated, from theoretical foundations to practical implementations. With a large number of illustrations and practical examples, this book serves as an excellent textbook or reference book for senior or graduate level courses on statistical signal/image processing, as well as a reference for researchers in related fields.

Minimax Theory Of Image Reconstruction

DOWNLOAD
Author : A. P. Korostelev
language : en
Publisher:
Release Date : 1993-04-16

Minimax Theory Of Image Reconstruction written by A. P. Korostelev and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-04-16 with categories.

Mathematical And Statistical Methods For Multistatic Imaging

DOWNLOAD
Author : Habib Ammari
language : en
Publisher: Springer
Release Date : 2013-11-29

Mathematical And Statistical Methods For Multistatic Imaging written by Habib Ammari and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-29 with Mathematics categories.

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.