Summary
In this work we show analytically and in real world experiments that an often used method for estimating subpixel edge positions in digital camera images generates a biased estimate of the edge position. The influence of this bias is as great as the uncertainty of edge positions due to camera noise. Many algorithms in computer vision rely on edge positions as input data. Some consider an uncertainty of the position due to camera noise. These algorithms can benefit from our calculation by adding our bias to their uncertainty.
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Mikulastik, P., HÖver, R., Urfalioglu, O. (2008). Error analysis of subpixel edge localisation. In: Damiani, E., Yétongnon, K., Schelkens, P., Dipanda, A., Legrand, L., Chbeir, R. (eds) Signal Processing for Image Enhancement and Multimedia Processing. Multimedia Systems and Applications Series, vol 31. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-72500-0_10
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DOI: https://doi.org/10.1007/978-0-387-72500-0_10
Publisher Name: Springer, Boston, MA
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