Image Registration (eBook)

Principles, Tools and Methods
eBook Download: PDF
2012 | 2012
XVIII, 442 Seiten
Springer London (Verlag)
978-1-4471-2458-0 (ISBN)

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Image Registration - A. Ardeshir Goshtasby
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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.
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 imaging.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.

IntroductionSimilarity and Dissimilarity MeasuresPoint DetectorsFeature ExtractionImage DescriptorsFeature Selection and Heterogeneous DescriptorsPoint Pattern MatchingRobust Parameter EstimationTransformation FunctionsImage Resampling and CompositingImage Registration MethodsA Principal Component Analysis (PCA)

Erscheint lt. Verlag 11.1.2012
Reihe/Serie Advances in Computer Vision and Pattern Recognition
Advances in Computer Vision and Pattern Recognition
Zusatzinfo XVIII, 442 p.
Verlagsort London
Sprache englisch
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte Feature Extraction and Selection • Image Resampling and Blending • Point Detectors and Descriptors • Point Matching • robust estimation • Similarity and Distance Measures • Transformation Functions
ISBN-10 1-4471-2458-8 / 1447124588
ISBN-13 978-1-4471-2458-0 / 9781447124580
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