Abstract
To recognize or identify objects it is desirable to use features which are minimally affected by changes in lighting and non-stationary noise. This requires accurate estimation of both signal and noise.
In response to this challenge, this paper proposes a method for estimation of non-stationary isotropic noise based on steering filters to directions perpendicular and parallel to the local signal. From the filter responses in this direction equations for signal and noise are obtained which lead to an edge detection method dependent solely upon local signal-to-noise ratio. The proposed method is compared to various common edge detection methods from the literature, on synthetic and real images. Quantitative improvement is demonstrated on synthetic images and qualitative improvement on real images.
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© 2006 Springer-Verlag Berlin Heidelberg
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Wyatt, P., Nakai, H. (2006). Applying Non-stationary Noise Estimation to Achieve Contrast Invariant Edge Detection. In: Narayanan, P.J., Nayar, S.K., Shum, HY. (eds) Computer Vision – ACCV 2006. ACCV 2006. Lecture Notes in Computer Science, vol 3852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11612704_74
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DOI: https://doi.org/10.1007/11612704_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31244-4
Online ISBN: 978-3-540-32432-4
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