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.
This text provides an introduction to image registration with particular emphasis on numerical methods in medical imaging. Designed for researchers in industry and academia, it should also be a suitable study guide for graduate mathematicians, computer scientists and medical physicists.
Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared. This is becoming the central tool for image analysis, understanding, and visualization in both medical and scientific applications. Medical Image Registration provid
This book provides a summary of current research in the application of image registration to satellite imagery. Presenting algorithms for creating mosaics and tracking changes on the planet's surface over time, it is an indispensable resource for researchers and advanced students in Earth and space science, and image processing.
To master the fundamentals of image registration, there is no more comprehensive source than 2-D and 3-D Image Registration. In addition to delving into the relevant theories of image registration, the author presents their underlying algorithms. You'll also discover cutting-edge techniques to use in remote sensing, industrial, and medical applications. Examples of image registration are presented throughout, and the companion Web site contains all the images used in the book and provides links to software and algorithms discussed in the text, allowing you to reproduce the results in the text and develop images for your own research needs. 2-D and 3-D Image Registration serves as an excellent textbook for classes in image registration as well as an invaluable working resource.
Whenever images taken at different times, from different viewpoints, and/or by different sensors need to be compared, merged, or integrated, image registration is required. Registration, also known as alignment, fusion, or warping, is the process of transforming data into a common reference frame. This book provides an overview of state-of-the-art registration techniques from theory to practice, numerous exercises, and via a supplementary Web page, free access to FAIR.m, a package that is based on the MATLAB software environment.
A hands-on guide to image registration theory and methods—with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods. It provides in-depth exploration of an array of fundamental issues, including image orientation detection, similarity measures, feature extraction methods, and elastic transformation functions. Also covered are robust parameter estimation, validation methods, multi-temporal and multi-modality image registration, methods for determining the orientation of an image, methods for identifying locally unique neighborhoods in an image, methods for detecting lines in an image, methods for finding corresponding points and corresponding lines in images, registration of video images to create panoramas, and much more. Theory and Applications of Image Registration provides readers with a practical guide to the theory and underpinning principles. Throughout the book numerous real-world examples are given, illustrating how image registration can be applied to problems in various fields, including biomedicine, remote sensing, and computer vision. Also provided are software routines to help readers develop their image registration skills. Many of the algorithms described in the book have been implemented, and the software packages are made available to the readers of the book on a companion website. In addition, the book: Explores the fundamentals of image registration and provides a comprehensive look at its multi-disciplinary applications Reviews real-world applications of image registration in the fields of biomedical imaging, remote sensing, computer vision, and more Discusses methods in the registration of long videos in target tracking and 3-D reconstruction Addresses key research topics and explores potential solutions to a number of open problems in image registration Includes a companion website featuring fully implemented algorithms and image registration software for hands-on learning Theory and Applications of Image Registration is a valuable resource for researchers and professionals working in industry and government agencies where image registration techniques are routinely employed. It is also an excellent supplementary text for graduate students in computer science, electrical engineering, software engineering, and medical physics.
The 2nd International Workshop on Biomedical Image Registration (WBIR) was held June 23–24, 2003, at the University of Pennsylvania, Philadelphia. Following the success of the ?rst workshop in Bled, Slovenia, this meeting aimed to once again bring together leading researchers in the area of biomedical image registration to present and discuss recent developments in the ?eld. Thetheory,implementationandapplicationofimageregistrationinmedicine have become major themes in nearly every scienti?c forum dedicated to image processingandanalysis. Thisintenseinterestre?ectsthe?eld’simportantrolein theconductofabroadandcontinuallygrowingrangeofstudies. Indeed,thete- niques have enabled some of the most exciting contemporary developments in the clinical and research application of medical imaging, including fusion of m- timodality data to assist clinical interpretation; change detection in longitudinal studies; brain shift modeling to improve anatomic localization in neurosurgical procedures; cardiac motion quanti?cation; construction of probabilistic atlases of organ structure and function; and large-scale phenotyping in animal models. WBIR was conceived to provide the burgeoning community of investigators in biomedical image registration an opportunity to share, discuss and stimulate developments in registration research and application at a meeting exclusively devoted to the topic. The format of this year’s workshop consisted of invited talks, author presentations and ample opportunities for discussion, the latter including an elegant reception and dinner hosted at the Mutter ̈ Museum. A representation of the best work in the ?eld, selected by peer review from full manuscripts,waspresentedinsingle-tracksessions. Thepapers,whichaddressed the full diversity of registration topics, are reproduced in this volume, along with enlightening essays by some of the invited speakers.
This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Biomedical Image Registration. The 20 revised full papers and 18 revised poster papers presented were carefully reviewed and selected for inclusion in the book. The papers cover all areas of biomedical image registration; methods of registration, biomedical applications, and validation of registration.
- Provides a comprehensive review of the literature in range image registration and serves as an effective study guide on this important topic - Presents a novel robust error measure, the surface interpretation, which is easily computed and offers significant immunity to non-Gaussian errors. The shortcomings of the least squares formalism in this setting are carefully explored - The first substantive work focusing on precision alignment, and the first capable of attaining such alignments in low-overlap scenarios without human intervention or manual prealignment - Offers extensive experimental results, highlighting both the impact of robust measures, and the relative efficiency of genetic search algorithms versus more traditional approaches. Extensive comparisons with more traditional algorithms and measures are presented
