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)
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.
Reviews a vast array of tools and methods, describing the underlying principles and comparing their performancesIncludes a glossary, an extensive list of references, and an appendix on principal component analysisProvides supplementary images and data in an associated website