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Added references on rotation invariance and filters.

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emmanuelle
2014-11-30 17:08:49 +01:00
parent 78e4d7a00d
commit 6f561130e6
1 changed files with 11 additions and 5 deletions
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doc/examples/plot_edge_filter.py
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@@ -36,11 +36,17 @@ plt.tight_layout()
Different operators compute different finite-difference approximations of the
gradient. For example, the Scharr filter results in a better rotational
variance than other filters such as the Sobel filter. The difference between
the two filters is illustrated below on an image that is the discretization of
a rotation-invariant continuous function. The discrepancy between the two
filters is stronger for regions of the image where the direction of the
gradient is close to diagonals, and for regions with high spatial frequencies.
variance than other filters such as the Sobel filter [1]_ [2]_. The difference
between the two filters is illustrated below on an image that is the
discretization of a rotation-invariant continuous function. The discrepancy
between the two filters is stronger for regions of the image where the
direction of the gradient is close to diagonal, and for regions with high
spatial frequencies.
.. [1] http://en.wikipedia.org/wiki/Sobel_operator#Alternative_operators
.. [2] B. Jaehne, H. Scharr, and S. Koerkel. Principles of filter design. In
Handbook of Computer Vision and Applications. Academic Press, 1999.
"""
x, y = np.ogrid[:100, :100]