Cantitate/Preț
Produs
Total produse
Vezi coșul
Image Registration: Principles, Tools and Methods de A. Ardeshir Goshtasby

Image Registration: Principles, Tools and Methods: Advances in Computer Vision and Pattern Recognition

Autor A. Ardeshir Goshtasby
en Limba Engleză Hardback – 13 ian 2012
This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 96636 lei  43-57 zile
  SPRINGER LONDON – 22 feb 2014 96636 lei  43-57 zile
Hardback (1) 97066 lei  43-57 zile
  SPRINGER LONDON – 13 ian 2012 97066 lei  43-57 zile

Din seria Advances in Computer Vision and Pattern Recognition

Preț: 97066 lei

Preț vechi: 121333 lei
-20% Nou

Puncte Express: 1456
Preț estimativ în valută:
18578€ • 19363$ • 15466£

Carte tipărită la comandă

Livrare economică 06-20 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781447124573
ISBN-10: 144712457X
Pagini: 487
Ilustrații: XVIII, 442 p.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.76 kg
Ediția:2012
Editura: SPRINGER LONDON
Colecția Springer
Seria Advances in Computer Vision and Pattern Recognition

Locul publicării:London, United Kingdom

Public țintă

Research

Cuprins

Introduction.- Similarity and Dissimilarity Measures.- Point Detectors.- Feature Extraction.- Image Descriptors.- Feature Selection and Heterogeneous Descriptors.- Point Pattern Matching.- Robust Parameter Estimation.- Transformation Functions.- Image Resampling and Compositing.- Image Registration Methods.- A Principal Component Analysis (PCA).

Recenzii

From the reviews:
“The book Image Registration: Principles, Tools and Methods by A. Ardeshir Goshtasby is a detailed reference on … low-level computer vision sub-tasks. … The book provides explicit near-pseudo-code descriptions of some of the algorithms discussed which can be helpful for someone interested in implementing the algorithms. It has a total of 441 pages and is self-contained and easy to read, thus well suited as a reference book for students and practitioners … .” (Zeeshan Zia, IAPR Newsletter, Vol. 35 (2), April, 2013)
“This book aims to describe principles, tools and methods in image registration. … New tools and methods are introduced and evaluated. The book covers the fundamentals of digital image registration … . Each chapter concludes with an extensive and … updated list of bibliographic references. This book is a valuable text for students, image analysis software developers, engineers, and researchers who would like to analyze two or more images of a scene.” (Oscar Bustos, Zentralblatt MATH, Vol. 1243, 2012)

Textul de pe ultima copertă

Image registration is the process of finding correspondence between all points in two images of a scene – a process with numerous applications in computer vision and image analysis.
This comprehensive text/reference presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data.
Topics and features:
  • Discusses a broad range of image analysis tools, including similarity/dissimilarity measures, point detectors, feature extraction and homogeneous descriptors, and feature selection and heterogeneous descriptors
  • Examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending
  • Covers a large number of image registration methods, such as principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods
  • Provides all images and data used in the book at the website http://www.imgfsr.com/book2.html, enabling the reader to reproduce the results
  • Includes a glossary, an extensive list of references, and an appendix on principal component analysis
An excellent reference for courses on image registration, image processing, computer vision, pattern recognition, and image analysis, this unique text/guide is also suitable for image analysis software developers, engineers, and researchers interested in analyzing two or more images of a scene.

Caracteristici

Reviews a vast array of tools and methods, describing the underlying principles and comparing their performances Includes a glossary, an extensive list of references, and an appendix on principal component analysis Provides supplementary images and data in an associated website Includes supplementary material: sn.pub/extras

Descriere

The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.