Abstract
We describe a dynamically based method for fitting an ellipse to noisy data, which has for interferometric applications a number of advantages over conventional static methods (originally developed for image processing). Our method relies on the observation that each data point belongs to an ordered time series and thus has a well-defined phase parameter. We demonstrate that for real experimental data it can achieve much greater accuracy than static methods. The precision of the fit is limited only by the statistical reliability of the data, even in extreme cases such as ellipses with a minor axis smaller than the measurement noise.
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