Abstract
The problem of robust parameter estimation in image registration is discussed and various robust methods for estimating registration parameters under outliers and inaccurate correspondences are reviewed and compared. After reviewing ordinary least-squares and weighted least-squares estimation, robust estimators such as maximum likelihood (M), repeated median (RM), scale (S), least median of squares (LMS), least trimmed square (LTS), and rank (R) estimators are described and compared.
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Goshtasby, A.A. (2012). Robust Parameter Estimation. In: Image Registration. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-2458-0_8
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