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DOI码：10.1016/j.optlaseng.2017.09.013
发表刊物：Optics and Lasers in Engineering
摘要：It is believed that the classic forward additive Newton–Raphson (FA-NR) algorithm and the recently introduced inverse compositional Gauss–Newton (IC-GN) algorithm give rise to roughly equal interpolation bias. Questioning the correctness of this statement, this paper presents a thorough analysis of interpolation bias for the IC-GN algorithm. A theoretical model is built to analytically characterize the dependence of interpolation bias upon speckle image, target image interpolation, and reference image gradient estimation. The interpolation biases of the FA-NR algorithm and the IC-GN algorithm can be significantly different, whose relative difference can exceed 80%. For the IC-GN algorithm, the gradient estimator can strongly affect the interpolation bias; the relative difference can reach 178%. Since the mean bias errors are insensitive to image noise, the theoretical model proposed remains valid in the presence of noise. To provide more implementation details, source codes are uploaded as a supplement.
论文类型：期刊论文
卷号：100
页面范围：267-278
是否译文：否
发表时间：2018-01-01
收录刊物：SCI
发布期刊链接：https://www.sciencedirect.com/science/article/abs/pii/S014381661730341X?via%3Dihub