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diff --git a/silx/image/utils.py b/silx/image/utils.py
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+# -*- coding: utf-8 -*-
+# /*##########################################################################
+# Copyright (C) 2019 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ############################################################################*/
+
+import numpy as np
+from math import ceil
+
+def gaussian_kernel(sigma, cutoff=4, force_odd_size=False):
+    """
+    Generates a Gaussian convolution kernel.
+
+    :param sigma: Standard Deviation of the Gaussian curve.
+    :param cutoff: Parameter tuning the truncation of the Gaussian.
+        The higher cutoff, the biggest the array will be (and the closest to
+        a "true" Gaussian function).
+    :param force_odd_size: when set to True, the resulting array will always
+        have an odd size, regardless of the values of "sigma" and "cutoff".
+    :return: a numpy.ndarray containing the truncated Gaussian function.
+        The array size is 2*c*s+1 where c=cutoff, s=sigma.
+
+    Nota: due to the quick decay of the Gaussian function, small values of the
+        "cutoff" parameter are usually fine. The energy difference between a
+        Gaussian truncated to [-c, c] and a "true" one is
+            erfc(c/(sqrt(2)*s))
+        so choosing cutoff=4*sigma keeps the truncation error below 1e-4.
+    """
+    size = int(ceil(2 * cutoff * sigma + 1))
+    if force_odd_size and size % 2 == 0:
+        size += 1
+    x = np.arange(size) - (size - 1.0) / 2.0
+    g = np.exp(-(x / sigma) ** 2 / 2.0)
+    g /= g.sum()
+    return g