diff --git a/skimage/feature/censure_cy.pyx b/skimage/feature/censure_cy.pyx
index 1c352fde..f8c712f8 100644
--- a/skimage/feature/censure_cy.pyx
+++ b/skimage/feature/censure_cy.pyx
@@ -18,55 +18,57 @@ def _censure_dob_loop(Py_ssize_t n,
     cdef Py_ssize_t n2 = 2 * n
     cdef double total_weight = inner_weight + outer_weight
 
-    # top-left pixel
-    inner = (integral_img[n2 + n, n2 + n]
-             + integral_img[n2 - n - 1, n2 - n - 1]
-             - integral_img[n2 + n, n2 - n - 1]
-             - integral_img[n2 - n - 1, n2 + n])
+    with nogil:
 
-    outer = integral_img[2 * n2, 2 * n2]
+        # top-left pixel
+        inner = (integral_img[n2 + n, n2 + n]
+                 + integral_img[n2 - n - 1, n2 - n - 1]
+                 - integral_img[n2 + n, n2 - n - 1]
+                 - integral_img[n2 - n - 1, n2 + n])
 
-    filtered_image[n2, n2] = (outer_weight * outer
-                              - total_weight * inner)
+        outer = integral_img[2 * n2, 2 * n2]
 
-    # left column
-    for i in range(n2 + 1, integral_img.shape[0] - n2):
-        inner = (integral_img[i + n, n2 + n]
-                 + integral_img[i - n - 1, n2 - n - 1]
-                 - integral_img[i + n, n2 - n - 1]
-                 - integral_img[i - n - 1, n2 + n])
+        filtered_image[n2, n2] = (outer_weight * outer
+                                  - total_weight * inner)
 
-        outer = (integral_img[i + n2, 2 * n2]
-                 - integral_img[i - n2 - 1, 2 * n2])
+        # left column
+        for i in range(n2 + 1, integral_img.shape[0] - n2):
+            inner = (integral_img[i + n, n2 + n]
+                     + integral_img[i - n - 1, n2 - n - 1]
+                     - integral_img[i + n, n2 - n - 1]
+                     - integral_img[i - n - 1, n2 + n])
 
-        filtered_image[i, n2] = (outer_weight * outer
-                                 - total_weight * inner)
+            outer = (integral_img[i + n2, 2 * n2]
+                     - integral_img[i - n2 - 1, 2 * n2])
 
-    # top row
-    for j in range(n2 + 1, integral_img.shape[1] - n2):
-        inner = (integral_img[n2 + n, j + n]
-                 + integral_img[n2 - n - 1, j - n - 1]
-                 - integral_img[n2 + n, j - n - 1]
-                 - integral_img[n2 - n - 1, j + n])
+            filtered_image[i, n2] = (outer_weight * outer
+                                     - total_weight * inner)
 
-        outer = (integral_img[2 * n2, j + n2]
-                 - integral_img[2 * n2, j - n2 - 1])
-
-        filtered_image[n2, j] = (outer_weight * outer
-                                 - total_weight * inner)
-
-    # remaining block
-    for i in range(n2 + 1, integral_img.shape[0] - n2):
+        # top row
         for j in range(n2 + 1, integral_img.shape[1] - n2):
-            inner = (integral_img[i + n, j + n]
-                     + integral_img[i - n - 1, j - n - 1]
-                     - integral_img[i + n, j - n - 1]
-                     - integral_img[i - n - 1, j + n])
+            inner = (integral_img[n2 + n, j + n]
+                     + integral_img[n2 - n - 1, j - n - 1]
+                     - integral_img[n2 + n, j - n - 1]
+                     - integral_img[n2 - n - 1, j + n])
 
-            outer = (integral_img[i + n2, j + n2]
-                     + integral_img[i - n2 - 1, j - n2 - 1]
-                     - integral_img[i + n2, j - n2 - 1]
-                     - integral_img[i - n2 - 1, j + n2])
+            outer = (integral_img[2 * n2, j + n2]
+                     - integral_img[2 * n2, j - n2 - 1])
 
-            filtered_image[i, j] = (outer_weight * outer
-                                    - total_weight * inner)
+            filtered_image[n2, j] = (outer_weight * outer
+                                     - total_weight * inner)
+
+        # remaining block
+        for i in range(n2 + 1, integral_img.shape[0] - n2):
+            for j in range(n2 + 1, integral_img.shape[1] - n2):
+                inner = (integral_img[i + n, j + n]
+                         + integral_img[i - n - 1, j - n - 1]
+                         - integral_img[i + n, j - n - 1]
+                         - integral_img[i - n - 1, j + n])
+
+                outer = (integral_img[i + n2, j + n2]
+                         + integral_img[i - n2 - 1, j - n2 - 1]
+                         - integral_img[i + n2, j - n2 - 1]
+                         - integral_img[i - n2 - 1, j + n2])
+
+                filtered_image[i, j] = (outer_weight * outer
+                                        - total_weight * inner)
diff --git a/skimage/feature/tests/test_censure.py b/skimage/feature/tests/test_censure.py
index 95bfcda3..ecd8a90f 100644
--- a/skimage/feature/tests/test_censure.py
+++ b/skimage/feature/tests/test_censure.py
@@ -2,6 +2,7 @@ import numpy as np
 from numpy.testing import assert_array_equal, assert_raises
 from skimage.data import moon
 from skimage.feature import CENSURE
+from skimage._shared.testing import test_parallel
 
 
 img = moon()
@@ -53,6 +54,7 @@ def test_keypoints_censure_moon_image_dob():
     assert_array_equal(expected_scales, detector.scales)
 
 
+@test_parallel()
 def test_keypoints_censure_moon_image_octagon():
     """Verify the actual Censure keypoints and their corresponding scale with
     the expected values for Octagon filter."""