diff --git a/skimage/__init__.py b/skimage/__init__.py
index 673562a7..f5f97130 100644
--- a/skimage/__init__.py
+++ b/skimage/__init__.py
@@ -158,7 +158,7 @@ else:
 
 
 if sys.version.startswith('2.6'):
-    warnings.warn("Python 2.6 is deprecated and will not be supported in scikit-image 0.13+")
+    warnings.warn("Python 2.6 is deprecated and will not be supported in scikit-image 0.13+", stacklevel=2)
 
 
 del warnings, functools, osp, imp, sys
diff --git a/skimage/_shared/_warnings.py b/skimage/_shared/_warnings.py
index 78d38fbd..dfaee7de 100644
--- a/skimage/_shared/_warnings.py
+++ b/skimage/_shared/_warnings.py
@@ -7,6 +7,13 @@ import inspect
 import re
 
 
+def warn(*args, **kwargs):
+    """A version of `warnings.warn` with a default stacklevel of 2
+    """
+    kwargs.setdefault('stacklevel', 2)
+    warnings.warn(*args, **kwargs)
+
+
 @contextmanager
 def all_warnings():
     """
@@ -67,7 +74,7 @@ def all_warnings():
 @contextmanager
 def expected_warnings(matching):
     """Context for use in testing to catch known warnings matching regexes
-    
+
     Parameters
     ----------
     matching : list of strings or compiled regexes
@@ -84,10 +91,10 @@ def expected_warnings(matching):
     -----
     Uses `all_warnings` to ensure all warnings are raised.
     Upon exiting, it checks the recorded warnings for the desired matching
-    pattern(s).  
+    pattern(s).
     Raises a ValueError if any match was not found or an unexpected
-    warning was raised.  
-    Allows for three types of behaviors: "and", "or", and "optional" matches. 
+    warning was raised.
+    Allows for three types of behaviors: "and", "or", and "optional" matches.
     This is done to accomodate different build enviroments or loop conditions
     that may produce different warnings.  The behaviors can be combined.
     If you pass multiple patterns, you get an orderless "and", where all of the
diff --git a/skimage/_shared/utils.py b/skimage/_shared/utils.py
index cc688fd7..96bc0fd7 100644
--- a/skimage/_shared/utils.py
+++ b/skimage/_shared/utils.py
@@ -6,10 +6,10 @@ import types
 
 import six
 
-from ._warnings import all_warnings
+from ._warnings import all_warnings, warn
 
 __all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
-           'safe_as_int', 'assert_nD']
+           'safe_as_int', 'assert_nD', 'warn']
 
 
 class skimage_deprecation(Warning):
@@ -170,7 +170,7 @@ def _mode_deprecations(mode):
     """Used to update deprecated mode names in
     `skimage._shared.interpolation.pyx`."""
     if mode.lower() == 'nearest':
-        warnings.warn(skimage_deprecation(
+        warn(skimage_deprecation(
             "Mode 'nearest' has been renamed to 'edge'. Mode 'nearest' will be "
             "removed in a future release."))
         mode = 'edge'
diff --git a/skimage/color/colorlabel.py b/skimage/color/colorlabel.py
index 76cdd6f2..10d4e114 100644
--- a/skimage/color/colorlabel.py
+++ b/skimage/color/colorlabel.py
@@ -1,8 +1,8 @@
-import warnings
 import itertools
 
 import numpy as np
 
+from .._shared.utils import warn
 from .. import img_as_float
 from . import rgb_colors
 from .colorconv import rgb2gray, gray2rgb
@@ -148,7 +148,7 @@ def _label2rgb_overlay(label, image=None, colors=None, alpha=0.3,
             raise ValueError("`image` and `label` must be the same shape")
 
         if image.min() < 0:
-            warnings.warn("Negative intensities in `image` are not supported")
+            warn("Negative intensities in `image` are not supported")
 
         image = img_as_float(rgb2gray(image))
         image = gray2rgb(image) * image_alpha + (1 - image_alpha)
diff --git a/skimage/exposure/_adapthist.py b/skimage/exposure/_adapthist.py
index 62ce2ecd..b42f3169 100644
--- a/skimage/exposure/_adapthist.py
+++ b/skimage/exposure/_adapthist.py
@@ -19,7 +19,7 @@ import numpy as np
 from .. import img_as_float, img_as_uint
 from ..color.adapt_rgb import adapt_rgb, hsv_value
 from ..exposure import rescale_intensity
-from .._shared.utils import skimage_deprecation, warnings
+from .._shared.utils import skimage_deprecation, warn
 
 NR_OF_GREY = 2 ** 14  # number of grayscale levels to use in CLAHE algorithm
 
@@ -77,9 +77,9 @@ def equalize_adapthist(image, ntiles_x=8, ntiles_y=8, clip_limit=0.01,
     image = rescale_intensity(image, out_range=(0, NR_OF_GREY - 1))
 
     if kernel_size is None:
-        warnings.warn('`ntiles_*` have been deprecated in favor of '
-                      '`kernel_size`.  The `ntiles_*` keyword arguments '
-                      'will be removed in v0.14', skimage_deprecation)
+        warn('`ntiles_*` have been deprecated in favor of '
+             '`kernel_size`.  The `ntiles_*` keyword arguments '
+             'will be removed in v0.14', skimage_deprecation)
         ntiles_x = ntiles_x or 8
         ntiles_y = ntiles_y or 8
         kernel_size = (np.round(image.shape[0] / ntiles_y),
diff --git a/skimage/exposure/exposure.py b/skimage/exposure/exposure.py
index 49b59c2b..9cdb03d1 100644
--- a/skimage/exposure/exposure.py
+++ b/skimage/exposure/exposure.py
@@ -1,9 +1,9 @@
 from __future__ import division
-import warnings
 import numpy as np
 
 from ..color import rgb2gray
 from ..util.dtype import dtype_range, dtype_limits
+from .._shared.utils import warn
 
 
 __all__ = ['histogram', 'cumulative_distribution', 'equalize_hist',
@@ -60,9 +60,9 @@ def histogram(image, nbins=256):
     """
     sh = image.shape
     if len(sh) == 3 and sh[-1] < 4:
-        warnings.warn("This might be a color image. The histogram will be "
-                      "computed on the flattened image. You can instead "
-                      "apply this function to each color channel.")
+        warn("This might be a color image. The histogram will be "
+             "computed on the flattened image. You can instead "
+             "apply this function to each color channel.")
 
     # For integer types, histogramming with bincount is more efficient.
     if np.issubdtype(image.dtype, np.integer):
@@ -292,12 +292,12 @@ def rescale_intensity(image, in_range='image', out_range='dtype'):
     if in_range is None:
         in_range = 'image'
         msg = "`in_range` should not be set to None. Use {!r} instead."
-        warnings.warn(msg.format(in_range))
+        warn(msg.format(in_range))
 
     if out_range is None:
         out_range = 'dtype'
         msg = "`out_range` should not be set to None. Use {!r} instead."
-        warnings.warn(msg.format(out_range))
+        warn(msg.format(out_range))
 
     imin, imax = intensity_range(image, in_range)
     omin, omax = intensity_range(image, out_range, clip_negative=(imin >= 0))
diff --git a/skimage/filters/_gaussian.py b/skimage/filters/_gaussian.py
index ad4e621d..2a455fe9 100644
--- a/skimage/filters/_gaussian.py
+++ b/skimage/filters/_gaussian.py
@@ -1,10 +1,10 @@
 import collections as coll
 import numpy as np
 from scipy import ndimage as ndi
-import warnings
 
 from ..util import img_as_float
 from ..color import guess_spatial_dimensions
+from .._shared.utils import warn
 
 __all__ = ['gaussian']
 
@@ -91,7 +91,7 @@ def gaussian(image, sigma, output=None, mode='nearest', cval=0,
         msg = ("Images with dimensions (M, N, 3) are interpreted as 2D+RGB "
                "by default. Use `multichannel=False` to interpret as "
                "3D image with last dimension of length 3.")
-        warnings.warn(RuntimeWarning(msg))
+        warn(RuntimeWarning(msg))
         multichannel = True
     if np.any(np.asarray(sigma) < 0.0):
         raise ValueError("Sigma values less than zero are not valid")
diff --git a/skimage/filters/rank/generic.py b/skimage/filters/rank/generic.py
index 5c6a352b..ec369153 100644
--- a/skimage/filters/rank/generic.py
+++ b/skimage/filters/rank/generic.py
@@ -16,17 +16,16 @@ References
 
 """
 
-import warnings
 import numpy as np
 from ... import img_as_ubyte
-from ..._shared.utils import assert_nD
+from ..._shared.utils import assert_nD, warn
 
 from . import generic_cy
 
 
 __all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean',
-           'geometric_mean', 'subtract_mean', 'median', 'minimum', 'modal', 
-           'enhance_contrast', 'pop', 'threshold', 'tophat', 'noise_filter', 
+           'geometric_mean', 'subtract_mean', 'median', 'minimum', 'modal',
+           'enhance_contrast', 'pop', 'threshold', 'tophat', 'noise_filter',
            'entropy', 'otsu']
 
 
@@ -65,8 +64,8 @@ def _handle_input(image, selem, out, mask, out_dtype=None, pixel_size=1):
 
     bitdepth = int(np.log2(max_bin))
     if bitdepth > 10:
-        warnings.warn("Bitdepth of %d may result in bad rank filter "
-                      "performance due to large number of bins." % bitdepth)
+        warn("Bitdepth of %d may result in bad rank filter "
+             "performance due to large number of bins." % bitdepth)
 
     return image, selem, out, mask, max_bin
 
@@ -377,7 +376,7 @@ def geometric_mean(image, selem, out=None, mask=None, shift_x=False, shift_y=Fal
 
     References
     ----------
-    .. [1] Gonzalez, R. C. and Wood, R. E. "Digital Image Processing (3rd Edition)." 
+    .. [1] Gonzalez, R. C. and Wood, R. E. "Digital Image Processing (3rd Edition)."
            Prentice-Hall Inc, 2006.
 
     """
diff --git a/skimage/filters/thresholding.py b/skimage/filters/thresholding.py
index 943041b8..331ea3f4 100644
--- a/skimage/filters/thresholding.py
+++ b/skimage/filters/thresholding.py
@@ -7,8 +7,7 @@ __all__ = ['threshold_adaptive',
 import numpy as np
 from scipy import ndimage as ndi
 from ..exposure import histogram
-from .._shared.utils import assert_nD
-import warnings
+from .._shared.utils import assert_nD, warn
 
 
 def threshold_adaptive(image, block_size, method='gaussian', offset=0,
@@ -130,7 +129,7 @@ def threshold_otsu(image, nbins=256):
     if image.shape[-1] in (3, 4):
         msg = "threshold_otsu is expected to work correctly only for " \
               "grayscale images; image shape {0} looks like an RGB image"
-        warnings.warn(msg.format(image.shape))
+        warn(msg.format(image.shape))
 
     # Check if the image is multi-colored or not
     if image.min() == image.max():
diff --git a/skimage/future/graph/_ncut.py b/skimage/future/graph/_ncut.py
index acdade69..faa8591d 100644
--- a/skimage/future/graph/_ncut.py
+++ b/skimage/future/graph/_ncut.py
@@ -1,8 +1,8 @@
 try:
     import networkx as nx
 except ImportError:
-    import warnings
-    warnings.warn('RAGs require networkx')
+    from ..._shared.utils import warn
+    warn('RAGs require networkx')
 import numpy as np
 from scipy import sparse
 from . import _ncut_cy
diff --git a/skimage/future/graph/graph_cut.py b/skimage/future/graph/graph_cut.py
index 3b112b7e..3279bb7e 100644
--- a/skimage/future/graph/graph_cut.py
+++ b/skimage/future/graph/graph_cut.py
@@ -1,8 +1,9 @@
+
 try:
     import networkx as nx
 except ImportError:
-    import warnings
-    warnings.warn('RAGs require networkx')
+    from ..._shared.utils import warn
+    warn('RAGs require networkx')
 import numpy as np
 from . import _ncut
 from . import _ncut_cy
diff --git a/skimage/io/_io.py b/skimage/io/_io.py
index 614b0e23..fb3e6fbc 100644
--- a/skimage/io/_io.py
+++ b/skimage/io/_io.py
@@ -1,5 +1,4 @@
 from io import BytesIO
-import warnings
 
 import numpy as np
 import six
@@ -8,7 +7,7 @@ from ..io.manage_plugins import call_plugin
 from ..color import rgb2grey
 from .util import file_or_url_context
 from ..exposure import is_low_contrast
-from .._shared._warnings import all_warnings
+from .._shared.utils import all_warnings, warn
 
 
 __all__ = ['imread', 'imread_collection', 'imsave', 'imshow', 'show']
@@ -129,7 +128,7 @@ def imsave(fname, arr, plugin=None, **plugin_args):
         if fname.lower().endswith(('.tiff', '.tif')):
             plugin = 'tifffile'
     if is_low_contrast(arr):
-        warnings.warn('%s is a low contrast image' % fname)
+        warn('%s is a low contrast image' % fname)
     return call_plugin('imsave', fname, arr, plugin=plugin, **plugin_args)
 
 
diff --git a/skimage/io/_plugins/matplotlib_plugin.py b/skimage/io/_plugins/matplotlib_plugin.py
index a9754a72..154317cd 100644
--- a/skimage/io/_plugins/matplotlib_plugin.py
+++ b/skimage/io/_plugins/matplotlib_plugin.py
@@ -1,10 +1,10 @@
 from collections import namedtuple
 import numpy as np
-import warnings
 import matplotlib.pyplot as plt
 from ...util import dtype as dtypes
 from ...exposure import is_low_contrast
 from ...util.colormap import viridis
+from ..._shared.utils import warn
 
 _default_colormap = 'gray'
 _nonstandard_colormap = viridis
@@ -67,14 +67,14 @@ def _raise_warnings(image_properties):
     """
     ip = image_properties
     if ip.unsupported_dtype:
-        warnings.warn("Non-standard image type; displaying image with "
-                      "stretched contrast.")
+        warn("Non-standard image type; displaying image with "
+             "stretched contrast.")
     if ip.low_dynamic_range:
-        warnings.warn("Low image dynamic range; displaying image with "
-                      "stretched contrast.")
+        warn("Low image dynamic range; displaying image with "
+             "stretched contrast.")
     if ip.out_of_range_float:
-        warnings.warn("Float image out of standard range; displaying "
-                      "image with stretched contrast.")
+        warn("Float image out of standard range; displaying "
+             "image with stretched contrast.")
 
 
 def _get_display_range(image):
diff --git a/skimage/io/_plugins/qt_plugin.py b/skimage/io/_plugins/qt_plugin.py
index 4d061933..ad869851 100644
--- a/skimage/io/_plugins/qt_plugin.py
+++ b/skimage/io/_plugins/qt_plugin.py
@@ -1,3 +1,4 @@
+from ..._shared import warn
 from .util import prepare_for_display, window_manager
 import numpy as np
 
@@ -10,7 +11,6 @@ try:
                              QLabel, QMainWindow, QPixmap, QWidget)
     from PyQt4 import QtCore, QtGui
     import sip
-    import warnings
 
 except ImportError:
     window_manager._release('qt')
@@ -119,8 +119,7 @@ if sip.SIP_VERSION >= 0x040c00:
     # doesn't work with earlier versions
     imread = imread_qt
 else:
-    warnings.warn(RuntimeWarning(
-        "sip version too old. QT imread disabled"))
+    warn(RuntimeWarning("sip version too old. QT imread disabled"))
 
 
 def imshow(arr, fancy=False):
diff --git a/skimage/measure/_marching_cubes.py b/skimage/measure/_marching_cubes.py
index cd0e1b60..46d50c7c 100644
--- a/skimage/measure/_marching_cubes.py
+++ b/skimage/measure/_marching_cubes.py
@@ -1,5 +1,6 @@
 import numpy as np
 import scipy.ndimage as ndi
+from .._shared.utils import warn
 from . import _marching_cubes_cy
 
 
@@ -239,11 +240,9 @@ def correct_mesh_orientation(volume, verts, faces, spacing=(1., 1., 1.),
     skimage.measure.mesh_surface_area
 
     """
-    import warnings
-    warnings.warn(
-        DeprecationWarning("`correct_mesh_orientation` is deprecated for "
-                           "removal as `marching_cubes` now guarantess "
-                           "correct mesh orientation."))
+    warn(DeprecationWarning("`correct_mesh_orientation` is deprecated for "
+                            "removal as `marching_cubes` now guarantess "
+                            "correct mesh orientation."))
 
     verts = verts.copy()
     verts[:, 0] /= spacing[0]
diff --git a/skimage/measure/fit.py b/skimage/measure/fit.py
index b227d59f..360a5d6d 100644
--- a/skimage/measure/fit.py
+++ b/skimage/measure/fit.py
@@ -1,8 +1,7 @@
 import math
-import warnings
 import numpy as np
 from scipy import optimize
-from .._shared.utils import skimage_deprecation
+from .._shared.utils import skimage_deprecation, warn
 
 
 def _check_data_dim(data, dim):
@@ -27,8 +26,7 @@ class BaseModel(object):
 
     @property
     def _params(self):
-        warnings.warn('`_params` attribute is deprecated, '
-                      'use `params` instead.')
+        warn('`_params` attribute is deprecated, use `params` instead.')
         return self.params
 
 
@@ -61,8 +59,8 @@ class LineModel(BaseModel):
 
     def __init__(self):
         self.params = None
-        warnings.warn(skimage_deprecation('`LineModel` is deprecated, '
-                      'use `LineModelND` instead.'))
+        warn(skimage_deprecation('`LineModel` is deprecated, '
+             'use `LineModelND` instead.'))
 
     def estimate(self, data):
         """Estimate line model from data using total least squares.
diff --git a/skimage/morphology/misc.py b/skimage/morphology/misc.py
index 1a024f38..653c240d 100644
--- a/skimage/morphology/misc.py
+++ b/skimage/morphology/misc.py
@@ -1,7 +1,7 @@
 import numpy as np
 import functools
-import warnings
 from scipy import ndimage as ndi
+from .._shared.utils import warn
 from .selem import _default_selem
 
 # Our function names don't exactly correspond to ndimages.
@@ -37,8 +37,8 @@ def default_selem(func):
         return func(image, selem=selem, *args, **kwargs)
 
     return func_out
- 
-def _check_dtype_supported(ar): 
+
+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. "
@@ -119,8 +119,8 @@ def remove_small_objects(ar, min_size=64, connectivity=1, in_place=False):
                          "`skimage.morphology.label`.")
 
     if len(component_sizes) == 2:
-        warnings.warn("Only one label was provided to `remove_small_objects`. "
-                      "Did you mean to use a boolean array?")
+        warn("Only one label was provided to `remove_small_objects`. "
+             "Did you mean to use a boolean array?")
 
     too_small = component_sizes < min_size
     too_small_mask = too_small[ccs]
@@ -181,35 +181,35 @@ def remove_small_holes(ar, min_size=64, connectivity=1, in_place=False):
     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 
+    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)
-    
+        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/restoration/unwrap.py b/skimage/restoration/unwrap.py
index 14f1eafa..7c21edb7 100644
--- a/skimage/restoration/unwrap.py
+++ b/skimage/restoration/unwrap.py
@@ -1,7 +1,8 @@
 import numpy as np
-import warnings
 from six import string_types
 
+from .._shared.utils import warn
+
 from ._unwrap_1d import unwrap_1d
 from ._unwrap_2d import unwrap_2d
 from ._unwrap_3d import unwrap_3d
@@ -83,9 +84,9 @@ def unwrap_phase(image, wrap_around=False, seed=None):
         if wrap_around[0]:
             raise ValueError('`wrap_around` is not supported for 1D images')
     if image.ndim in (2, 3) and 1 in image.shape:
-        warnings.warn('Image has a length 1 dimension. Consider using an '
-                      'array of lower dimensionality to use a more efficient '
-                      'algorithm')
+        warn('Image has a length 1 dimension. Consider using an '
+             'array of lower dimensionality to use a more efficient '
+             'algorithm')
 
     if np.ma.isMaskedArray(image):
         mask = np.require(np.ma.getmaskarray(image), np.uint8, ['C'])
diff --git a/skimage/segmentation/_felzenszwalb.py b/skimage/segmentation/_felzenszwalb.py
index d9b82c2b..7a3e7758 100644
--- a/skimage/segmentation/_felzenszwalb.py
+++ b/skimage/segmentation/_felzenszwalb.py
@@ -1,6 +1,6 @@
-import warnings
 import numpy as np
 
+from .._shared.utils import warn
 from ._felzenszwalb_cy import _felzenszwalb_grey
 
 
@@ -56,8 +56,8 @@ def felzenszwalb(image, scale=1, sigma=0.8, min_size=20):
     # assume we got 2d image with multiple channels
     n_channels = image.shape[2]
     if n_channels != 3:
-        warnings.warn("Got image with %d channels. Is that really what you"
-                      " wanted?" % image.shape[2])
+        warn("Got image with %d channels. Is that really what you"
+             " wanted?" % image.shape[2])
     segmentations = []
     # compute quickshift for each channel
     for c in range(n_channels):
diff --git a/skimage/segmentation/random_walker_segmentation.py b/skimage/segmentation/random_walker_segmentation.py
index d3a6a759..7aee8088 100644
--- a/skimage/segmentation/random_walker_segmentation.py
+++ b/skimage/segmentation/random_walker_segmentation.py
@@ -8,10 +8,12 @@ Installing pyamg and using the 'cg_mg' mode of random_walker improves
 significantly the performance.
 """
 
-import warnings
 import numpy as np
 from scipy import sparse, ndimage as ndi
 
+from .._shared.utils import warn
+
+
 # executive summary for next code block: try to import umfpack from
 # scipy, but make sure not to raise a fuss if it fails since it's only
 # needed to speed up a few cases.
@@ -345,17 +347,17 @@ def random_walker(data, labels, beta=130, mode='bf', tol=1.e-3, copy=True,
             mode = 'bf'
 
     if UmfpackContext is None and mode == 'cg':
-        warnings.warn('"cg" mode will be used, but it may be slower than '
-                      '"bf" because SciPy was built without UMFPACK. Consider'
-                      ' rebuilding SciPy with UMFPACK; this will greatly '
-                      'accelerate the conjugate gradient ("cg") solver. '
-                      'You may also install pyamg and run the random_walker '
-                      'function in "cg_mg" mode (see docstring).')
+        warn('"cg" mode will be used, but it may be slower than '
+             '"bf" because SciPy was built without UMFPACK. Consider'
+             ' rebuilding SciPy with UMFPACK; this will greatly '
+             'accelerate the conjugate gradient ("cg") solver. '
+             'You may also install pyamg and run the random_walker '
+             'function in "cg_mg" mode (see docstring).')
 
     if (labels != 0).all():
-        warnings.warn('Random walker only segments unlabeled areas, where '
-                      'labels == 0. No zero valued areas in labels were '
-                      'found. Returning provided labels.')
+        warn('Random walker only segments unlabeled areas, where '
+             'labels == 0. No zero valued areas in labels were '
+             'found. Returning provided labels.')
 
         if return_full_prob:
             # Find and iterate over valid labels
@@ -438,8 +440,7 @@ def random_walker(data, labels, beta=130, mode='bf', tol=1.e-3, copy=True,
                       return_full_prob=return_full_prob)
     if mode == 'cg_mg':
         if not amg_loaded:
-            warnings.warn(
-                """pyamg (http://pyamg.org/)) is needed to use
+            warn("""pyamg (http://pyamg.org/)) is needed to use
                 this mode, but is not installed. The 'cg' mode will be used
                 instead.""")
             X = _solve_cg(lap_sparse, B, tol=tol,
diff --git a/skimage/segmentation/slic_superpixels.py b/skimage/segmentation/slic_superpixels.py
index adc21a65..b558f78a 100644
--- a/skimage/segmentation/slic_superpixels.py
+++ b/skimage/segmentation/slic_superpixels.py
@@ -3,8 +3,8 @@
 import collections as coll
 import numpy as np
 from scipy import ndimage as ndi
-import warnings
 
+from .._shared.utils import warn
 from ..util import img_as_float, regular_grid
 from ..segmentation._slic import (_slic_cython,
                                   _enforce_label_connectivity_cython)
@@ -111,8 +111,8 @@ def slic(image, n_segments=100, compactness=10., max_iter=10, sigma=0,
 
     """
     if enforce_connectivity is None:
-        warnings.warn('Deprecation: enforce_connectivity will default to'
-                      ' True in future versions.')
+        warn('Deprecation: enforce_connectivity will default to'
+             ' True in future versions.')
         enforce_connectivity = False
 
     image = img_as_float(image)
diff --git a/skimage/transform/_geometric.py b/skimage/transform/_geometric.py
index c9249444..1e06e8b5 100644
--- a/skimage/transform/_geometric.py
+++ b/skimage/transform/_geometric.py
@@ -1,12 +1,11 @@
 import six
 import math
-import warnings
 import numpy as np
 from scipy import spatial
 from scipy import ndimage as ndi
 
 from .._shared.utils import (get_bound_method_class, safe_as_int,
-                             _mode_deprecations)
+                             _mode_deprecations, warn)
 from ..util import img_as_float
 
 from ._warps_cy import _warp_fast
@@ -184,8 +183,7 @@ class ProjectiveTransform(GeometricTransform):
 
     @property
     def _matrix(self):
-        warnings.warn('`_matrix` attribute is deprecated, '
-                      'use `params` instead.')
+        warn('`_matrix` attribute is deprecated, use `params` instead.')
         return self.params
 
     @property
@@ -782,8 +780,7 @@ class PolynomialTransform(GeometricTransform):
 
     @property
     def _params(self):
-        warnings.warn('`_params` attribute is deprecated, '
-                      'use `params` instead.')
+        warn('`_params` attribute is deprecated, use `params` instead.')
         return self.params
 
     def estimate(self, src, dst, order=2):
@@ -1320,13 +1317,13 @@ def warp(image, inverse_map=None, map_args={}, output_shape=None, order=1,
     if order == 2:
         # When fixing this issue, make sure to fix the branches further
         # below in this function
-        warnings.warn("Bi-quadratic interpolation behavior has changed due "
-                      "to a bug in the implementation of scikit-image. "
-                      "The new version now serves as a wrapper "
-                      "around SciPy's interpolation functions, which itself "
-                      "is not verified to be a correct implementation. Until "
-                      "skimage's implementation is fixed, we recommend "
-                      "to use bi-linear or bi-cubic interpolation instead.")
+        warn("Bi-quadratic interpolation behavior has changed due "
+             "to a bug in the implementation of scikit-image. "
+             "The new version now serves as a wrapper "
+             "around SciPy's interpolation functions, which itself "
+             "is not verified to be a correct implementation. Until "
+             "skimage's implementation is fixed, we recommend "
+             "to use bi-linear or bi-cubic interpolation instead.")
 
     if order in (0, 1, 3) and not map_args:
         # use fast Cython version for specific interpolation orders and input
diff --git a/skimage/transform/integral.py b/skimage/transform/integral.py
index 91b07ac7..2ec7ab65 100644
--- a/skimage/transform/integral.py
+++ b/skimage/transform/integral.py
@@ -1,6 +1,8 @@
 import numpy as np
 import collections
-import warnings
+
+from .._shared.utils import warn
+
 
 def integral_image(img):
     """Integral image / summed area table.
@@ -81,10 +83,10 @@ def integrate(ii, start, end, *args):
         rows = start.shape[0]
     # handle deprecated input format
     else:
-        warnings.warn("The syntax 'integrate(ii, r0, c0, r1, c1)' is "
-                      "deprecated, and will be phased out in release 0.14. "
-                      "The new syntax is "
-                      "'integrate(ii, (r0, c0), (r1, c1))'.")
+        warn("The syntax 'integrate(ii, r0, c0, r1, c1)' is "
+             "deprecated, and will be phased out in release 0.14. "
+             "The new syntax is "
+             "'integrate(ii, (r0, c0), (r1, c1))'.")
         if isinstance(start, collections.Iterable):
             rows = len(start)
         args = (start, end) + args
diff --git a/skimage/viewer/__init__.py b/skimage/viewer/__init__.py
index 443e5659..f4b4c8ec 100644
--- a/skimage/viewer/__init__.py
+++ b/skimage/viewer/__init__.py
@@ -1,6 +1,6 @@
-import warnings
+from .._shared.utils import warn
 from .viewers import ImageViewer, CollectionViewer
 from .qt import has_qt
 
 if not has_qt:
-    warnings.warn('Viewer requires Qt')
+    warn('Viewer requires Qt')
diff --git a/skimage/viewer/utils/core.py b/skimage/viewer/utils/core.py
index 7f632d43..8bffaafe 100644
--- a/skimage/viewer/utils/core.py
+++ b/skimage/viewer/utils/core.py
@@ -1,14 +1,13 @@
-import warnings
-
 import numpy as np
 from ..qt import QtWidgets, has_qt, FigureManagerQT, FigureCanvasQTAgg
+from ..._shared.utils import warn
 import matplotlib as mpl
 from matplotlib.figure import Figure
 from matplotlib import _pylab_helpers
 from matplotlib.colors import LinearSegmentedColormap
 
 if has_qt and 'agg' not in mpl.get_backend().lower():
-    warnings.warn("Recommended matplotlib backend is `Agg` for full "
+    warn("Recommended matplotlib backend is `Agg` for full "
                   "skimage.viewer functionality.")