diff --git a/skimage/transform/__init__.py b/skimage/transform/__init__.py
index befcc23f..089487ee 100644
--- a/skimage/transform/__init__.py
+++ b/skimage/transform/__init__.py
@@ -6,6 +6,6 @@ from ._geometric import (warp, warp_coords, estimate_transform,
                          SimilarityTransform, AffineTransform,
                          ProjectiveTransform, PolynomialTransform,
                          PiecewiseAffineTransform)
-from ._warps import swirl, homography, resize, rotate, rescale
+from ._warps import swirl, resize, rotate, rescale
 from .pyramids import (pyramid_reduce, pyramid_expand,
                        pyramid_gaussian, pyramid_laplacian)
diff --git a/skimage/transform/_warps.py b/skimage/transform/_warps.py
index 0ace0937..7ac3e63f 100644
--- a/skimage/transform/_warps.py
+++ b/skimage/transform/_warps.py
@@ -253,101 +253,3 @@ def swirl(image, center=None, strength=1, radius=100, rotation=0,
     return warp(image, _swirl_mapping, map_args=warp_args,
                 output_shape=output_shape,
                 order=order, mode=mode, cval=cval)
-
-
-def homography(image, H, output_shape=None, order=1,
-               mode='constant', cval=0.):
-    """
-    .. note:: Deprecated in skimage 0.7
-        `homography` will be removed in skimage 0.8, it is replaced by
-        `warp` because the latter provides the same functionality::
-
-            warp(image, ProjectiveTransform(H))
-
-    Perform a projective transformation (homography) on an image.
-
-    For each pixel, given its homogeneous coordinate :math:`\mathbf{x}
-    = [x, y, 1]^T`, its target position is calculated by multiplying
-    with the given matrix, :math:`H`, to give :math:`H \mathbf{x}`.
-    E.g., to rotate by theta degrees clockwise, the matrix should be
-
-    ::
-
-      [[cos(theta) -sin(theta) 0]
-       [sin(theta)  cos(theta) 0]
-       [0            0         1]]
-
-    or, to translate x by 10 and y by 20,
-
-    ::
-
-      [[1 0 10]
-       [0 1 20]
-       [0 0 1 ]].
-
-    Parameters
-    ----------
-    image : 2-D array
-        Input image.
-    H : array of shape ``(3, 3)``
-        Transformation matrix H that defines the homography.
-    output_shape : tuple (rows, cols)
-        Shape of the output image generated.
-    order : int
-        Order of splines used in interpolation.
-    mode : string
-        How to handle values outside the image borders.  Passed as-is
-        to ndimage.
-    cval : string
-        Used in conjunction with mode 'constant', the value outside
-        the image boundaries.
-
-    Examples
-    --------
-    >>> # rotate by 90 degrees around origin and shift down by 2
-    >>> x = np.arange(9, dtype=np.uint8).reshape((3, 3)) + 1
-    >>> x
-    array([[1, 2, 3],
-           [4, 5, 6],
-           [7, 8, 9]], dtype=uint8)
-    >>> theta = -np.pi/2
-    >>> M = np.array([[np.cos(theta),-np.sin(theta),0],
-    ...               [np.sin(theta), np.cos(theta),2],
-    ...               [0,             0,            1]])
-    >>> x90 = homography(x, M, order=1)
-    >>> x90
-    array([[3, 6, 9],
-           [2, 5, 8],
-           [1, 4, 7]], dtype=uint8)
-    >>> # translate right by 2 and down by 1
-    >>> y = np.zeros((5,5), dtype=np.uint8)
-    >>> y[1, 1] = 255
-    >>> y
-    array([[  0,   0,   0,   0,   0],
-           [  0, 255,   0,   0,   0],
-           [  0,   0,   0,   0,   0],
-           [  0,   0,   0,   0,   0],
-           [  0,   0,   0,   0,   0]], dtype=uint8)
-    >>> M = np.array([[ 1.,  0.,  2.],
-    ...               [ 0.,  1.,  1.],
-    ...               [ 0.,  0.,  1.]])
-    >>> y21 = homography(y, M, order=1)
-    >>> y21
-    array([[  0,   0,   0,   0,   0],
-           [  0,   0,   0,   0,   0],
-           [  0,   0,   0, 255,   0],
-           [  0,   0,   0,   0,   0],
-           [  0,   0,   0,   0,   0]], dtype=uint8)
-
-    """
-    import warnings
-    warnings.warn('the homography function is deprecated; '
-                  'use the `warp` and `ProjectiveTransform` class instead',
-                  category=DeprecationWarning)
-
-    tform = ProjectiveTransform(H)
-    return warp(image, inverse_map=tform.inverse, output_shape=output_shape,
-                order=order, mode=mode, cval=cval)
-
-    return warp(image, inverse_map=tform.inverse, output_shape=output_shape,
-                order=order, mode=mode, cval=cval)
diff --git a/skimage/transform/tests/test_warps.py b/skimage/transform/tests/test_warps.py
index 2cdda001..93f87320 100644
--- a/skimage/transform/tests/test_warps.py
+++ b/skimage/transform/tests/test_warps.py
@@ -5,7 +5,7 @@ from scipy.ndimage import map_coordinates
 from skimage.transform import (warp, warp_coords, rotate, resize, rescale,
                                AffineTransform,
                                ProjectiveTransform,
-                               SimilarityTransform, homography)
+                               SimilarityTransform)
 from skimage import transform as tf, data, img_as_float
 from skimage.color import rgb2gray
 
@@ -39,10 +39,6 @@ def test_homography():
     assert_array_almost_equal(x90, np.rot90(x))
 
 
-def test_homography_basic():
-    homography(np.random.random((25, 25)), np.eye(3))
-
-
 def test_fast_homography():
     img = rgb2gray(data.lena()).astype(np.uint8)
     img = img[:, :100]
@@ -87,10 +83,10 @@ def test_rotate():
 
 def test_rotate_resize():
     x = np.zeros((10, 10), dtype=np.double)
-    
+
     x45 = rotate(x, 45, resize=False)
     assert x45.shape == (10, 10)
-    
+
     x45 = rotate(x, 45, resize=True)
     # new dimension should be d = sqrt(2 * (10/2)^2)
     assert x45.shape == (14, 14)