4.2 Quantitative comparison of ambiguity removal algorithms

Metcalf et al. (2006Jump To The Next Citation Point) compared several algorithms and implementations quantitatively with the help of two synthetic data sets, a flux-rope simulation by Fan and Gibson (2004Jump To The Next Citation Point) and a multipolar constant-α structure computed with the Chiu and Hilton (1977Jump To The Next Citation Point) linear force-free code. The results of the different ambiguity removal techniques have been compared with a number of metrics (see Table II in Metcalf et al., 2006Jump To The Next Citation Point). For the discussion here we concentrate only on the first test case (flux rope) and the area metrics, which simply tells for what fraction of pixels the ambiguity has been removed correctly. A value of 1 corresponds to a perfect result and 0.5 to random. The result is visualized in Figure 7View Image, where the ambiguity has been removed correctly in black areas. Wrong pixels are white. In the following, we briefly describe the basic features of these methods and provide the performance (fraction of pixels with correctly removed ambiguity).
View Image

Figure 7: Overview of the performance of different algorithms for removing the 180° azimuth ambiguity. The codes have been applied to synthetic data (a flux-rope simulation by Fan and Gibson, 2004Jump To The Next Citation Point). In black areas the codes found the correct azimuth and in white areas not. Image reproduced by permission from Figure 3 of Metcalf et al. (2006Jump To The Next Citation Point), copyright by Springer.

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