Image Registration

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  • Topic: Computer vision, Feature detection, Image processing
  • Pages : 62 (21804 words )
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  • Published : April 28, 2013
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ICIP 2005 Tutorial

Image Registration: A Survey and Recent Advances

Presented by

Barbara Zitov´ a Jan Flusser ˇ Filip Sroubek

Institute of Information Theory and Automation Academy of Sciences of the Czech Republic Pod vod´renskou vˇˇ´ 4, 182 08 Prague 8, Czech Republic a ezı E-mail: {zitova,flusser,sroubekf}@utia.cas.cz

This is complementary material for ICIP’05 tutorial ”Image Registration: A Survey and Recent Advances”. It aims to present a review of recent as well as classic image registration methods. Image registration is the process of overlaying two or more images of the same scene taken at different times, under different lighting conditions, from different viewpoints and/or by different sensors. The major registration purpose is to remove or suppress geometric distortions between the reference and sensed images. Image registration is a crucial step in all image analysis tasks in which the final information is gained by combining various data sources. Image registration is required, among others, in remote sensing (multispectral classification, image fusion, environmental monitoring, change detection, image mosaicing, weather forecasting, integrating information into GIS), in medicine (combining CT and NMR data to obtain more complete information about the patient, monitoring of tumor growth, comparison of the patient data with anatomical atlases), in cartography (map updating), and in military applications (target localization, missile navigation). Keywords: Image registration, feature detection, feature matching, mapping function, resampling

Part I: Survey
1 Introduction

Image registration is the process of overlaying two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. It geometrically aligns two images - the reference and sensed images. The present differences between images are introduced due to different imaging conditions. Image registration is a crucial step in all image analysis tasks in which the final information is gained from the combination of various data sources like in image fusion, change detection, and multichannel image restoration. Typically, registration is required in remote sensing (multispectral classification, environmental monitoring, change detection, image mosaicing, weather forecasting, creating super-resolution images, integrating information into geographic information systems - GIS), in medicine (combining CT and NMR data to obtain more complete information about the patient, monitoring tumor growth, treatment verification, comparison of the patient’s data with anatomical atlases), in cartography (map updating), and in computer vision (target localization, automatic quality control), to name a few. During the last decades, image acquisition devices have undergone rapid development and growing amount and diversity of obtained images invoked the research on automatic image registration. A comprehensive survey of image registration methods was published in 1992 by Brown [26]. This material is based on the survey [237] covering relevant approaches introduced later and in this way mapping the current development of registration techniques. According to the database of the Institute of Scientific Information (ISI), in the last ten years more than 1000 papers were published on the topic of image registration. Methods published before 1992 that became classic or introduced key ideas, which are still in use, are included as well to retain the continuity and to give complete view of image registration research. We do not contemplate to go into details of particular algorithms or describe results of comparative experiments, rather we want to summarize main approaches and point out interesting parts of the registration methods. In Section 2 various aspects and problems of image registration will be discussed. Both area-based and feature-based approaches to feature selection are described in Section 3. Section 4 reviews...
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