diff --git a/skimage/filter/_gabor.py b/skimage/filter/_gabor.py
index 3424e12f..02210a8f 100644
--- a/skimage/filter/_gabor.py
+++ b/skimage/filter/_gabor.py
@@ -2,7 +2,7 @@ import numpy as np
 from scipy import ndimage
 
 
-def gabor_kernel(sigmax, sigmay, frequency, theta, offset=0):
+def gabor_kernel(sigma_x, sigma_y, frequency, theta, offset=0):
     """Build complex 2D Gabor filter kernel.
 
     Frequency and orientation representations of the Gabor filter are similar to
@@ -11,9 +11,9 @@ def gabor_kernel(sigmax, sigmay, frequency, theta, offset=0):
 
     Parameters
     ----------
-    sigmax : float
+    sigma_x : float
         Standard deviation in x-direction.
-    sigmay : float
+    sigma_y : float
         Standard deviation in y-direction.
     frequency : float
         Frequency of the harmonic function.
@@ -34,22 +34,22 @@ def gabor_kernel(sigmax, sigmay, frequency, theta, offset=0):
 
     """
 
-    x0 = np.ceil(max(3 * sigmax, 1))
-    y0 = np.ceil(max(3 * sigmay, 1))
+    x0 = np.ceil(max(3 * sigma_x, 1))
+    y0 = np.ceil(max(3 * sigma_y, 1))
     y, x = np.mgrid[-y0:y0+1, -x0:x0+1]
 
     rotx = x * np.cos(theta) + y * np.sin(theta)
     roty = -x * np.sin(theta) + y * np.cos(theta)
 
     g = np.zeros(y.shape, dtype=np.complex)
-    g[:] = np.exp(-0.5 * (rotx**2 / sigmax**2 + roty**2 / sigmay**2))
-    g /= 2 * np.pi * sigmax * sigmay
+    g[:] = np.exp(-0.5 * (rotx**2 / sigma_x**2 + roty**2 / sigma_y**2))
+    g /= 2 * np.pi * sigma_x * sigma_y
     g *= np.exp(1j * (2 * np.pi * frequency * rotx + offset))
 
     return g
 
 
-def gabor_filter(image, sigmax, sigmay, frequency, theta, offset=0,
+def gabor_filter(image, sigma_x, sigma_y, frequency, theta, offset=0,
                  mode='reflect', cval=0):
     """Perform Gabor filtering.
 
@@ -62,9 +62,9 @@ def gabor_filter(image, sigmax, sigmay, frequency, theta, offset=0,
 
     Parameters
     ----------
-    sigmax : float
+    sigma_x : float
         Standard deviation in x-direction.
-    sigmay : float
+    sigma_y : float
         Standard deviation in y-direction.
     frequency : float
         Frequency of the harmonic function.
@@ -86,7 +86,7 @@ def gabor_filter(image, sigmax, sigmay, frequency, theta, offset=0,
 
     """
 
-    g = gabor_kernel(sigmax, sigmay, frequency, theta, offset)
+    g = gabor_kernel(sigma_x, sigma_y, frequency, theta, offset)
 
     filtered_real = ndimage.convolve(image, np.real(g), mode=mode, cval=cval)
     filtered_imag = ndimage.convolve(image, np.imag(g), mode=mode, cval=cval)