diff --git a/skimage/segmentation/quickshift.py b/skimage/segmentation/quickshift.pyx
similarity index 77%
rename from skimage/segmentation/quickshift.py
rename to skimage/segmentation/quickshift.pyx
index 65c8847f..8bec6d2b 100644
--- a/skimage/segmentation/quickshift.py
+++ b/skimage/segmentation/quickshift.pyx
@@ -1,8 +1,10 @@
 import numpy as np
+cimport numpy as np
+
 from itertools import product
 
 
-def quickshift(image, sigma=5, tau=10):
+def quickshift(np.ndarray[dtype=np.float_t, ndim=3, mode="c"] image, sigma=5, tau=10):
     """Computes quickshift clustering in RGB-(x,y) space.
 
     Parameters
@@ -31,37 +33,38 @@ def quickshift(image, sigma=5, tau=10):
     # window size for neighboring pixels to consider
     if sigma < 1:
         raise ValueError("Sigma should be >= 1")
-    w = int(2 * sigma)
+    cdef int w = int(2 * sigma)
+    
+    cdef int width = image.shape[0]
+    cdef int height = image.shape[1]
 
-    width, height = image.shape[:2]
-    densities = np.zeros((width, height))
+    cdef np.ndarray[dtype=np.float_t, ndim=2] densities = np.zeros((width, height))
 
     # compute densities
     for x, y in product(xrange(width), xrange(height)):
-        current_pixel = np.hstack([image[x, y, :], x, y])
+        current_pixel = image[x, y, :]
         for xx, yy in product(xrange(-w / 2, w / 2 + 1), repeat=2):
             x_, y_ = x + xx, y + yy
             if 0 <= x_ < width and 0 <= y_ < height:
-                other_pixel = np.hstack([image[x_, y_, :], x_, y_])
-                dist = np.sum((current_pixel - other_pixel) ** 2)
+                dist = np.sum((current_pixel - image[x_, y_, :])**2) + (x - x_)**2 + (y - y_)**2
                 densities[x, y] += np.exp(-dist / sigma)
 
     # this will break ties that otherwise would give us headache
-    densities += np.random.normal(scale=0.00001, size=densities.shape)
+
+    densities += np.random.normal(scale=0.00001, size=(width, height))
     # default parent to self:
     parent = np.arange(width * height).reshape(width, height)
     dist_parent = np.zeros((width, height))
     # find nearest node with higher density
     for x, y in product(xrange(width), xrange(height)):
         current_density = densities[x, y]
-        current_pixel = np.hstack([image[x, y, :], x, y])
+        current_pixel = image[x, y, :]
         closest = np.inf
         for xx, yy in product(xrange(-w / 2, w / 2 + 1), repeat=2):
             x_, y_ = x + xx, y + yy
             if 0 <= x_ < width and 0 <= y_ < height:
                 if densities[x_, y_] > current_density:
-                    other_pixel = np.hstack([image[x_, y_, :], x_, y_])
-                    dist = np.sum((current_pixel - other_pixel) ** 2)
+                    dist = np.sum((current_pixel - image[x_, y_, :])**2) + (x - x_)**2 + (y - y_)**2
                     if dist < closest:
                         closest = dist
                         parent[x, y] = x_ * width + y_
diff --git a/skimage/segmentation/setup.py b/skimage/segmentation/setup.py
index 8f6361bf..b6f8d1e2 100644
--- a/skimage/segmentation/setup.py
+++ b/skimage/segmentation/setup.py
@@ -5,23 +5,27 @@ from skimage._build import cython
 
 base_path = os.path.abspath(os.path.dirname(__file__))
 
+
 def configuration(parent_package='', top_path=None):
     from numpy.distutils.misc_util import Configuration, get_numpy_include_dirs
 
     config = Configuration('segmentation', parent_package, top_path)
 
-    cython(['felzenszwalb.pyx'], working_path=base_path)
-    config.add_extension('felzenszwalb', sources=['felzenszwalb.c'],
+    #cython(['felzenszwalb.pyx'], working_path=base_path)
+    #config.add_extension('felzenszwalb', sources=['felzenszwalb.c'],
+                         #include_dirs=[get_numpy_include_dirs()])
+    cython(['quickshift.pyx'], working_path=base_path)
+    config.add_extension('quickshift', sources=['quickshift.c'],
                          include_dirs=[get_numpy_include_dirs()])
 
     return config
 
 if __name__ == '__main__':
     from numpy.distutils.core import setup
-    setup(maintainer = 'scikits-image Developers',
-          maintainer_email = 'scikits-image@googlegroups.com',
-          description = 'Segmentation Algorithms',
-          url = 'https://github.com/scikits-image/scikits-image',
-          license = 'SciPy License (BSD Style)',
+    setup(maintainer='scikits-image Developers',
+          maintainer_email='scikits-image@googlegroups.com',
+          description='Segmentation Algorithms',
+          url='https://github.com/scikits-image/scikits-image',
+          license='SciPy License (BSD Style)',
           **(configuration(top_path='').todict())
           )