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A review of image-warping methods

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  • C. A. Glasbey
  • K. V. Mardia

Abstract

Image warping is a transformation which maps all positions in one image plane to positions in a second plane. It arises in many image analysis problems, whether in order to remove optical distortions introduced by a camera or a particular viewing perspective, to register an image with a map or template, or to align two or more images. The choice of warp is a compromise between a smooth distortion and one which achieves a good match. Smoothness can be ensured by assuming a parametric form for the warp or by constraining it using differential equations. Matching can be specified by points to be brought into alignment, by local measures of correlation between images, or by the coincidence of edges. Parametric and non-parametric approaches to warping, and matching criteria, are reviewed.

Suggested Citation

  • C. A. Glasbey & K. V. Mardia, 1998. "A review of image-warping methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(2), pages 155-171.
    • Handle: RePEc:taf:japsta:v:25:y:1998:i:2:p:155-171
    DOI: 10.1080/02664769823151
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    Cited by:

    1. Mohammed Bennani Dosse & Jos Berge, 2010. "Anisotropic Orthogonal Procrustes Analysis," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 111-128, March.
    2. R. G. Aykroyd & K. V. Mardia, 2003. "A wavelet approach to shape analysis for spinal curves," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(6), pages 605-623.
    3. A. E. Madrid & J. M. Angulo & J. Mateu, 2016. "Point Pattern Analysis of Spatial Deformation and Blurring Effects on Exceedances," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 512-530, September.

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