Skip to main content

Introduction

  • Chapter

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

The problem of image registration is described and steps involved in registering various types of images are given. The chapter also covers the history of image registration and its evolution during the past century.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Anuta, P.E.: Registration of multispectral video imagery. Soc. Photo-Opt. Instrum. Eng. J. 7, 168–175 (1969)

    Google Scholar 

  2. Anuta, P.E.: Spatial registration of multispectral and multitemporal digital imagery using fast Fourier transform techniques. IEEE Trans. Geosci. Electron. 8(4), 353–368 (1970)

    Article  Google Scholar 

  3. Barber, D.C.: Automatic alignment of radionuclide images. Phys. Med. Biol. 27, 387–396 (1982)

    Article  Google Scholar 

  4. Barnea, D.I., Silverman, H.F.: A class of algorithms for fast digital image registration. IEEE Trans. Comput. 21(2), 179–186 (1972)

    Article  MATH  Google Scholar 

  5. Becker, J.: Focusing Camera. US Patent 1,178,474, Filed 11 Aug. 1900; Patented 4 Apr. 1916

    Google Scholar 

  6. Chum, O., Matas, J.: Optimal randomized RANSAC. IEEE Trans. Pattern Anal. Mach. Intell. 30(8), 1472–1482 (2008)

    Article  Google Scholar 

  7. Dressler, R.: Image Matching Apparatus. US Patent 2,989,890, Filed 13 Nov. 1956; Patented 27 June 1961

    Google Scholar 

  8. Gerlot, P., Bizais, Y.: Image registration: a review and a strategy for medical applications. In: de Graaf, C.N., Viergever, M.A. (eds.) Information Processing in Medical Imaging, pp. 81–89. Plenum Press, New York (1988)

    Google Scholar 

  9. Goshtasby, A.: Piecewise linear mapping functions for image registration. Pattern Recognit. 19(6), 459–466 (1986)

    Article  Google Scholar 

  10. Goshtasby, A.: Piecewise cubic mapping functions for image registration. Pattern Recognit. 20(5), 525–533 (1987)

    Article  Google Scholar 

  11. Goshtasby, A.: Geometric correction of satellite images using composite transformation functions. In: Proc. Twenty First Int’l Sym. Remote Sensing of Environment, October, pp. 825–834 (1987)

    Google Scholar 

  12. Goshtasby, A.: Registration of image with geometric distortion. IEEE Trans. Geosci. Remote Sens. 26(1), 60–64 (1988)

    Article  Google Scholar 

  13. Goshtasby, A.: Image registration by local approximation methods. Image Vis. Comput. 6(4), 255–261 (1988)

    Article  Google Scholar 

  14. Johnson, H.R.: Dual-Image Registration System. US Patent 3,636,254, Filed 12 Nov. 1969; Patented 18 Jan. 1972

    Google Scholar 

  15. Kelley, W.V.D., Mason, J.: Photographic Printing. US Patent 1,350,023, Filed 26 Jul. 1917, Patented 17 Aug. 1920

    Google Scholar 

  16. Leese, J.A., Novak, G.S., Clark, B.B.: An automatic technique for obtaining cloud motion from geosynchronous satellite data using cross correlation. Appl. Meteorol. 10, 110–132 (1971)

    Article  Google Scholar 

  17. Levine, M.D., O’Handley, D.O., Yagi, G.M.: Computer determination of depth maps. Comput. Graph. Image Process. 2, 131–150 (1973)

    Article  Google Scholar 

  18. Link, T.V., Smith, R.H.: Cathod Ray Tube Image Matching Apparatus. US Patent 3,290,546, Filed 25 Oct. 1962; Patented 6 Dec. 1966

    Google Scholar 

  19. Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.: Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imaging 16(2), 187–198 (1997)

    Article  Google Scholar 

  20. Maintz, J.B.A., Viergever, M.A.: A survey of medical image registration. Med. Image Anal. 2(1), 1–36 (1988)

    Article  Google Scholar 

  21. Matas, J., Chum, O.: Randomized RANSAC with Td:d test. Image Vis. Comput. 22(10), 837–842 (2004)

    Article  Google Scholar 

  22. Maurer, C.R. Jr., Fitzpatrick, J.M. A review of medical image registration. In: Interactive Image-Guided Neurosurgery, pp. 17–44 (1993)

    Google Scholar 

  23. Mori, K.I., Kidode, M., Asada, H.: An iterative prediction and correction method for automatic stereocomparison. Comput. Graph. Image Process. 2, 393–401 (1973)

    Article  Google Scholar 

  24. Nevatia, R.: Depth measurement by motion stereo. Comput. Graph. Image Process. 15, 203–214 (1976)

    Article  Google Scholar 

  25. Pluim, J.P.W., Maintz, J.B.A., Viergever, M.A.: Mutual-information-based image registration of medical images: A survey. IEEE Trans. Med. Imaging 22(8), 986–1004 (2003)

    Article  Google Scholar 

  26. Pratt, W.K.: Correlation techniques for image registration. IEEE Trans. Aerosp. Electron. Syst. 10(3), 353–358 (1974)

    Article  Google Scholar 

  27. Roberts, L.G.: Machine Perception of 3-D Solids. Ph.D. Thesis, MIT (1963)

    Google Scholar 

  28. Rohr, K.: Landmark-Based Image Analysis: Using Geometric and Intensity Models. Kluwer Academic, Boston (2001)

    Book  MATH  Google Scholar 

  29. Seaman, O.J.L.: Method of Producing Composite Photographs. US Patent 2,314,663, Filed 23 Dec. 1937; Patented 17 Dec. 1940

    Google Scholar 

  30. Singh, M., Frei, W., Shibata, T., Huth, G.C.: A digital technique for accurate change detection in nuclear medical images with application to myocardial perfusion studies using Thallium-201. IEEE Trans. Nucl. Sci. 26, 565–575 (1979)

    Article  Google Scholar 

  31. Steiner, W.L.: Electron Image Correlator Tube. US Patent 3,424,937, Filed 8 Jan. 1965; Patented 28 Jan. 1969

    Google Scholar 

  32. Studholme, C., Hill, D.L.G., Hawkes, D.J.: Automated 3D registration of truncated MR and CT images of the head. In: Proc. British Machine Vision Conf., pp. 27–36 (1995)

    Google Scholar 

  33. Tuytelaars, T., Mikolajczyk, K.: Local invariant feature detectors: A survey. Found. Trends Comput. Graph. Vis. 3(3), 177–280 (2007)

    Article  Google Scholar 

  34. van den Elsen, P.A., Pol, E.-J.D., Viergever, M.A.: Medical image matching: A review with classification. In: IEEE Engineering in Medicine and Biology, pp. 26–39 (1993)

    Google Scholar 

  35. Venot, A., Devaux, J.Y., Herbin, M., Lebruchec, J.F., Dubertret, L., Raulo, Y., Roucayrol, J.C.: An automated system for the registration and comparison of photographic images in medicine. IEEE Trans. Med. Imaging 7(4), 298–303 (1988)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Ardeshir Goshtasby .

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag London Limited

About this chapter

Cite this chapter

Goshtasby, A.A. (2012). Introduction. In: Image Registration. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-2458-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-2458-0_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-2457-3

  • Online ISBN: 978-1-4471-2458-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics