diff --git a/skimage/morphology/__init__.py b/skimage/morphology/__init__.py
index 9bf311c4..159a4ac2 100644
--- a/skimage/morphology/__init__.py
+++ b/skimage/morphology/__init__.py
@@ -8,7 +8,7 @@ from .watershed import watershed
 from ._skeletonize import skeletonize, medial_axis
 from .convex_hull import convex_hull_image, convex_hull_object
 from .greyreconstruct import reconstruction
-from .misc import remove_small_objects
+from .misc import remove_small_objects, remove_small_holes
 
 from ..measure._label import label
 from .._shared.utils import deprecated as _deprecated
@@ -40,4 +40,5 @@ __all__ = ['binary_erosion',
            'convex_hull_image',
            'convex_hull_object',
            'reconstruction',
-           'remove_small_objects']
+           'remove_small_objects',
+           'remove_small_holes']
diff --git a/skimage/morphology/misc.py b/skimage/morphology/misc.py
index e743a398..1a024f38 100644
--- a/skimage/morphology/misc.py
+++ b/skimage/morphology/misc.py
@@ -37,7 +37,12 @@ def default_selem(func):
         return func(image, selem=selem, *args, **kwargs)
 
     return func_out
-
+ 
+def _check_dtype_supported(ar): 
+    # Should use `issubdtype` for bool below, but there's a bug in numpy 1.7
+    if not (ar.dtype == bool or np.issubdtype(ar.dtype, np.integer)):
+        raise TypeError("Only bool or integer image types are supported. "
+                        "Got %s." % ar.dtype)
 
 def remove_small_objects(ar, min_size=64, connectivity=1, in_place=False):
     """Remove connected components smaller than the specified size.
@@ -88,10 +93,8 @@ def remove_small_objects(ar, min_size=64, connectivity=1, in_place=False):
     >>> d is a
     True
     """
-    # Should use `issubdtype` for bool below, but there's a bug in numpy 1.7
-    if not (ar.dtype == bool or np.issubdtype(ar.dtype, np.integer)):
-        raise TypeError("Only bool or integer image types are supported. "
-                        "Got %s." % ar.dtype)
+    # Raising type error if not int or bool
+    _check_dtype_supported(ar)
 
     if in_place:
         out = ar
@@ -124,3 +127,89 @@ def remove_small_objects(ar, min_size=64, connectivity=1, in_place=False):
     out[too_small_mask] = 0
 
     return out
+
+def remove_small_holes(ar, min_size=64, connectivity=1, in_place=False):
+    """Remove continguous holes smaller than the specified size.
+
+    Parameters
+    ----------
+    ar : ndarray (arbitrary shape, int or bool type)
+        The array containing the connected components of interest.
+    min_size : int, optional (default: 64)
+        The hole component size.
+    connectivity : int, {1, 2, ..., ar.ndim}, optional (default: 1)
+        The connectivity defining the neighborhood of a pixel.
+    in_place : bool, optional (default: False)
+        If `True`, remove the connected components in the input array itself.
+        Otherwise, make a copy.
+
+    Raises
+    ------
+    TypeError
+        If the input array is of an invalid type, such as float or string.
+    ValueError
+        If the input array contains negative values.
+
+    Returns
+    -------
+    out : ndarray, same shape and type as input `ar`
+        The input array with small holes within connected components removed.
+
+    Examples
+    --------
+    >>> from skimage import morphology
+    >>> a = np.array([[1, 1, 1, 1, 1, 0],
+    ...               [1, 1, 1, 0, 1, 0],
+    ...               [1, 0, 0, 1, 1, 0],
+    ...               [1, 1, 1, 1, 1, 0]], bool)
+    >>> b = morphology.remove_small_holes(a, 2)
+    >>> b
+    array([[ True,  True,  True,  True,  True, False],
+           [ True,  True,  True,  True,  True, False],
+           [ True, False, False,  True,  True, False],
+           [ True,  True,  True,  True,  True, False]], dtype=bool)
+    >>> c = morphology.remove_small_holes(a, 2, connectivity=2)
+    >>> c
+    array([[ True,  True,  True,  True,  True, False],
+           [ True,  True,  True, False,  True, False],
+           [ True, False, False,  True,  True, False],
+           [ True,  True,  True,  True,  True, False]], dtype=bool)
+    >>> d = morphology.remove_small_holes(a, 2, in_place=True)
+    >>> d is a
+    True
+
+    Notes
+    -----
+
+    If the array type is int, it is assumed that it contains already-labeled 
+    objects. The labels are not kept in the output image (this function always 
+    outputs a bool image). It is suggested that labeling is completed after 
+    using this function.
+    """
+    _check_dtype_supported(ar)
+    
+    #Creates warning if image is an integer image
+    if ar.dtype != bool:
+        warnings.warn("Any labeled images will be returned as a boolean array. "
+                      "Did you mean to use a boolean array?", UserWarning)
+    
+    if in_place:
+        out = ar
+    else:
+        out = ar.copy()
+        
+    #Creating the inverse of ar
+    if in_place:
+        out = np.logical_not(out,out)
+    else:
+        out = np.logical_not(out)
+    
+    #removing small objects from the inverse of ar
+    out = remove_small_objects(out, min_size, connectivity, in_place)
+    
+    if in_place:
+        out = np.logical_not(out,out)
+    else:
+        out = np.logical_not(out)
+    
+    return out
diff --git a/skimage/morphology/tests/test_misc.py b/skimage/morphology/tests/test_misc.py
index 8789b22a..b7222cb5 100644
--- a/skimage/morphology/tests/test_misc.py
+++ b/skimage/morphology/tests/test_misc.py
@@ -1,7 +1,8 @@
 import numpy as np
 from numpy.testing import (assert_array_equal, assert_equal, assert_raises,
                            assert_warns)
-from skimage.morphology import remove_small_objects
+from skimage.morphology import remove_small_objects, remove_small_holes
+from ..._shared._warnings import expected_warnings
 
 test_image = np.array([[0, 0, 0, 1, 0],
                        [1, 1, 1, 0, 0],
@@ -60,7 +61,8 @@ def test_single_label_warning():
     image = np.array([[0, 0, 0, 1, 0],
                       [1, 1, 1, 0, 0],
                       [1, 1, 1, 0, 0]], int)
-    assert_warns(UserWarning, remove_small_objects, image, min_size=6)
+    with expected_warnings(['use a boolean array?']):
+        remove_small_objects(image, min_size=6)
 
 
 def test_float_input():
@@ -72,6 +74,102 @@ def test_negative_input():
     negative_int = np.random.randint(-4, -1, size=(5, 5))
     assert_raises(ValueError, remove_small_objects, negative_int)
 
+test_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
+                             [0,1,1,1,1,1,0,0,0,0],
+                             [0,1,0,0,1,1,0,0,0,0],
+                             [0,1,1,1,0,1,0,0,0,0],
+                             [0,1,1,1,1,1,0,0,0,0],
+                             [0,0,0,0,0,0,0,1,1,1],
+                             [0,0,0,0,0,0,0,1,0,1],
+                             [0,0,0,0,0,0,0,1,1,1]], bool)
 
+def test_one_connectivity_holes():
+    expected = np.array([[0,0,0,0,0,0,1,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1]], bool)
+    observed = remove_small_holes(test_holes_image, min_size=3)
+    assert_array_equal(observed, expected)
+
+
+def test_two_connectivity_holes():
+    expected = np.array([[0,0,0,0,0,0,1,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,0,0,1,1,0,0,0,0],
+                         [0,1,1,1,0,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1]], bool)
+    observed = remove_small_holes(test_holes_image, min_size=3, connectivity=2)
+    assert_array_equal(observed, expected)
+
+def test_in_place_holes():
+    observed = remove_small_holes(test_holes_image, min_size=3, in_place=True)
+    assert_equal(observed is test_holes_image, True,
+        "remove_small_holes in_place argument failed.")
+
+def test_labeled_image_holes():
+    labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,1,0,0,1,1,0,0,0,0],
+                                    [0,1,1,1,0,1,0,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,0,0,0,0,0,0,2,2,2],
+                                    [0,0,0,0,0,0,0,2,0,2],
+                                    [0,0,0,0,0,0,0,2,2,2]], dtype=int)
+    expected = np.array([[0,0,0,0,0,0,1,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1]], dtype=bool)
+    observed = remove_small_holes(labeled_holes_image, min_size=3)
+    assert_array_equal(observed, expected)
+
+
+def test_uint_image_holes():
+    labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,1,0,0,1,1,0,0,0,0],
+                                    [0,1,1,1,0,1,0,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,0,0,0,0,0,0,2,2,2],
+                                    [0,0,0,0,0,0,0,2,0,2],
+                                    [0,0,0,0,0,0,0,2,2,2]], dtype=np.uint8)
+    expected = np.array([[0,0,0,0,0,0,1,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,1,1,1,1,1,0,0,0,0],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1],
+                         [0,0,0,0,0,0,0,1,1,1]], dtype=bool)
+    observed = remove_small_holes(labeled_holes_image, min_size=3)
+    assert_array_equal(observed, expected)
+
+
+def test_label_warning_holes():
+    labeled_holes_image = np.array([[0,0,0,0,0,0,1,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,1,0,0,1,1,0,0,0,0],
+                                    [0,1,1,1,0,1,0,0,0,0],
+                                    [0,1,1,1,1,1,0,0,0,0],
+                                    [0,0,0,0,0,0,0,2,2,2],
+                                    [0,0,0,0,0,0,0,2,0,2],
+                                    [0,0,0,0,0,0,0,2,2,2]], dtype=int)
+    with expected_warnings(['use a boolean array?']):
+        remove_small_holes(labeled_holes_image, min_size=3)
+
+def test_float_input_holes():
+    float_test = np.random.rand(5, 5)
+    assert_raises(TypeError, remove_small_holes, float_test)
+  
 if __name__ == "__main__":
     np.testing.run_module_suite()