diff --git a/CONTRIBUTORS.txt b/CONTRIBUTORS.txt
index 8528002b..44214d85 100644
--- a/CONTRIBUTORS.txt
+++ b/CONTRIBUTORS.txt
@@ -234,3 +234,6 @@
 
 - Kirill Malev
   Frangi and Hessian filters implementation
+
+- Abdeali Kothari
+  Alpha blending to convert from rgba to rgb
diff --git a/doc/source/user_guide/transforming_image_data.rst b/doc/source/user_guide/transforming_image_data.rst
index 79c6e03a..817e8190 100644
--- a/doc/source/user_guide/transforming_image_data.rst
+++ b/doc/source/user_guide/transforming_image_data.rst
@@ -42,6 +42,17 @@ transformed to floating-point type by the conversion operation::
 
 
 
+Conversion from RGBA to RGB - Removing alpha channel through alpha blending
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Converting an RGBA image to an RGB image by alpha blending it with a
+background is realized with :func:`rgba2rgb` :: 
+
+    >>> from skimage.color import rgba2rgb
+    >>> from skimage import data
+    >>> img_rgba = data.horse()
+    >>> img_rgb = rgba2rgb(img_rgba)
+
 Conversion between color and gray values
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
diff --git a/skimage/color/__init__.py b/skimage/color/__init__.py
index 80d8a03a..fe4c71bc 100644
--- a/skimage/color/__init__.py
+++ b/skimage/color/__init__.py
@@ -1,5 +1,6 @@
 from .colorconv import (convert_colorspace,
                         guess_spatial_dimensions,
+                        rgba2rgb,
                         rgb2hsv,
                         hsv2rgb,
                         rgb2xyz,
diff --git a/skimage/color/colorconv.py b/skimage/color/colorconv.py
index e8dd4224..29baa91e 100644
--- a/skimage/color/colorconv.py
+++ b/skimage/color/colorconv.py
@@ -156,6 +156,70 @@ def _prepare_colorarray(arr):
     return dtype.img_as_float(arr)
 
 
+def _prepare_rgba_array(arr):
+    """Check the shape of the array to be RGBA and convert it to
+    floating point representation.
+
+    """
+    arr = np.asanyarray(arr)
+
+    if arr.ndim not in [3, 4] or arr.shape[-1] != 4:
+        msg = ("the input array must have a shape == (.., ..,[ ..,] 4)), "
+               "got {0}".format(arr.shape))
+        raise ValueError(msg)
+
+    return dtype.img_as_float(arr)
+
+
+def rgba2rgb(rgba, background=(1, 1, 1)):
+    """RGBA to RGB conversion.
+
+    Parameters
+    ----------
+    rgba : array_like
+        The image in RGBA format, in a 3-D array of shape ``(.., .., 4)``.
+    background : array_like
+        The color of the background to blend the image with. A tuple
+        containing 3 floats between 0 to 1 - the RGB value of the background.
+
+    Returns
+    -------
+    out : ndarray
+        The image in RGB format, in a 3-D array of shape ``(.., .., 3)``.
+
+    Raises
+    ------
+    ValueError
+        If `rgba` is not a 3-D array of shape ``(.., .., 4)``.
+
+    References
+    ----------
+    .. [1] https://en.wikipedia.org/wiki/Alpha_compositing#Alpha_blending
+
+    Examples
+    --------
+    >>> from skimage import color
+    >>> from skimage import data
+    >>> img_rgba = data.horse()
+    >>> img_rgb = color.rgba2rgb(img_rgba)
+    """
+    arr = _prepare_rgba_array(rgba)
+    if isinstance(background, tuple) and len(background) != 3:
+        raise ValueError('the background must be a tuple with 3 items - the '
+                         'RGB color of the background. Got {0} items.'
+                         .format(len(background)))
+
+    alpha = arr[..., -1]
+    channels = arr[..., :-1]
+    out = np.empty_like(channels)
+
+    for ichan in range(channels.shape[-1]):
+        out[..., ichan] = np.clip(
+            (1 - alpha) * background[ichan] + alpha * channels[..., ichan],
+            a_min=0, a_max=1)
+    return out
+
+
 def rgb2hsv(rgb):
     """RGB to HSV color space conversion.
 
diff --git a/skimage/color/tests/test_colorconv.py b/skimage/color/tests/test_colorconv.py
index 106eabee..6cb1aa84 100644
--- a/skimage/color/tests/test_colorconv.py
+++ b/skimage/color/tests/test_colorconv.py
@@ -41,6 +41,7 @@ from skimage.color import (rgb2hsv, hsv2rgb,
                            rgb2yiq, yiq2rgb,
                            rgb2ypbpr, ypbpr2rgb,
                            rgb2ycbcr, ycbcr2rgb,
+                           rgba2rgb,
                            guess_spatial_dimensions
                            )
 
@@ -67,6 +68,9 @@ class TestColorconv(TestCase):
 
     img_rgb = imread(os.path.join(data_dir, 'color.png'))
     img_grayscale = imread(os.path.join(data_dir, 'camera.png'))
+    img_rgba = np.array([[[0, 0.5, 1, 0],
+                          [0, 0.5, 1, 1],
+                          [0, 0.5, 1, 0.5]]]).astype(np.float)
 
     colbars = np.array([[1, 1, 0, 0, 1, 1, 0, 0],
                         [1, 1, 1, 1, 0, 0, 0, 0],
@@ -95,6 +99,22 @@ class TestColorconv(TestCase):
                           [[46.228, -43.774, 56.589]],   # green
                           ])
 
+    # RGBA to RGB
+    def test_rgba2rgb_conversion(self):
+        rgba = self.img_rgba
+        rgb = rgba2rgb(rgba)
+        expected = np.array([[[1, 1, 1],
+                              [0, 0.5, 1],
+                              [0.5, 0.75, 1]]]).astype(np.float)
+        self.assertEqual(rgb.shape, expected.shape)
+        assert_almost_equal(rgb, expected)
+
+    def test_rgba2rgb_error_grayscale(self):
+        self.assertRaises(ValueError, rgba2rgb, self.img_grayscale)
+
+    def test_rgba2rgb_error_rgb(self):
+        self.assertRaises(ValueError, rgba2rgb, self.img_rgb)
+
     # RGB to HSV
     def test_rgb2hsv_conversion(self):
         rgb = img_as_float(self.img_rgb)[::16, ::16]