Foundations and Trends® in Computer Graphics and Vision > Vol 2 > Issue 1

Image Alignment and Stitching: A Tutorial

Richard Szeliski, Microsoft Research, USA, szeliski@microsoft.com
 
Suggested Citation
Richard Szeliski (2007), "Image Alignment and Stitching: A Tutorial", Foundations and TrendsĀ® in Computer Graphics and Vision: Vol. 2: No. 1, pp 1-104. http://dx.doi.org/10.1561/0600000009

Published: 02 Jan 2007
© 2006 R. Szeliski
 
Subjects
Feature detection and selection,  Image restoration and enhancement,  3D reconstruction and image-based modeling
 

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In this article:
1. Introduction
2. Motion Models
3. Direct (pixel-based) Alignment
4. Feature-Based Registration
5. Global Registration
6. Compositing
7. Extensions and Open Issues
References

Abstract

This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It ends with a discussion of open research problems in the area.

DOI:10.1561/0600000009
ISBN: 978-1-933019-04-8
116 pp. $75.00
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ISBN: 978-1-933019-99-4
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Table of contents:
1. Introduction
2. Motion Models
3. Direct (pixel-based) Alignment
4. Feature-based Registration
5. Global Registration
6. Compositing
7. Extensions and open issues
References

Image Alignment and Stitching

Image Alignment and Stitching: A Tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures.

Image Alignment and Stitching: A Tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It closes with a discussion of open research problems in the area.

Image Alignment and Stitching: A Tutorial is an invaluable resource for anyone planning or conducting research in this particular area, or computer vision generally. The essentials of the topic are presented in a tutorial style and an extensive bibliography guides towards further reading.

 
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