diff --git a/skimage/transform/_warps.py b/skimage/transform/_warps.py
index 5af3afa6..7ac3e63f 100644
--- a/skimage/transform/_warps.py
+++ b/skimage/transform/_warps.py
@@ -253,98 +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)