diff --git a/CHANGELOG b/CHANGELOG
index d0e2c660797c..dcd185a3e47e 100644
--- a/CHANGELOG
+++ b/CHANGELOG
@@ -1,3 +1,7 @@
+2014-04-22 Added an example showing the difference between 
+	   interpolation = 'none' and interpolation = 'nearest' in
+	   `imshow()` when saving vector graphics files.
+
 2014-04-10 Fixed the triangular marker rendering error. The "Up" triangle was
            rendered instead of "Right" triangle and vice-versa.
 
diff --git a/examples/images_contours_and_fields/interpolation_none_vs_nearest.py b/examples/images_contours_and_fields/interpolation_none_vs_nearest.py
new file mode 100644
index 000000000000..eaa7d3332574
--- /dev/null
+++ b/examples/images_contours_and_fields/interpolation_none_vs_nearest.py
@@ -0,0 +1,62 @@
+"""
+Displays the difference between interpolation = 'none' and 
+interpolation = 'nearest'.
+
+Interpolation = 'none' and interpolation = 'nearest' are equivalent when 
+converting a figure to an image file, such as a PNG.  
+Interpolation = 'none' and interpolation = 'nearest' behave quite 
+differently, however, when converting a figure to a vector graphics file, 
+such as a PDF.  As shown, Interpolation = 'none' works well when a big 
+image is scaled down, while interpolation = 'nearest' works well when a 
+small image is blown up.
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.cbook as cbook
+
+#Load big image
+big_im_path = cbook.get_sample_data('necked_tensile_specimen.png')
+big_im = plt.imread(big_im_path)
+#Define small image
+small_im = np.array([[0.25, 0.75, 1.0, 0.75], [0.1, 0.65, 0.5, 0.4], \
+    [0.6, 0.3, 0.0, 0.2], [0.7, 0.9, 0.4, 0.6]])
+
+#Create a 2x2 table of plots
+fig = plt.figure(figsize = [8.0, 7.5])
+ax = plt.subplot(2,2,1)
+ax.imshow(big_im, interpolation = 'none')
+ax = plt.subplot(2,2,2)
+ax.imshow(big_im, interpolation = 'nearest')
+ax = plt.subplot(2,2,3)
+ax.imshow(small_im, interpolation = 'none')
+ax = plt.subplot(2,2,4)
+ax.imshow(small_im, interpolation = 'nearest')
+plt.subplots_adjust(left = 0.24, wspace = 0.2, hspace = 0.1, \
+    bottom = 0.05, top = 0.86)
+
+#Label the rows and columns of the table
+fig.text(0.03, 0.645, 'Big Image\nScaled Down', ha = 'left')
+fig.text(0.03, 0.225, 'Small Image\nBlown Up', ha = 'left')
+fig.text(0.383, 0.90, "Interpolation = 'none'", ha = 'center')
+fig.text(0.75, 0.90, "Interpolation = 'nearest'", ha = 'center')
+
+#If you were going to run this example on your local machine, you 
+#would save the figure as a PNG, save the same figure as a PDF, and 
+#then compare them.  The following code would suffice.
+txt = fig1.text(0.452, 0.95, 'Saved as a PNG', fontsize = 18)
+# plt.savefig('None_vs_nearest-png.png')
+# txt.set_text('Saved as a PDF')
+# plt.savefig('None_vs_nearest-pdf.pdf')
+
+#Here, however, we need to display the PDF on a webpage, which means
+#the PDF must be converted into an image.  For the purposes of this 
+#example, the 'Nearest_vs_none-pdf.pdf' has been pre-converted into 
+#'Nearest_vs_none-pdf.png' at 80 dpi.  We simply need to load and
+#display it.
+pdf_im_path = cbook.get_sample_data('None_vs_nearest-pdf.png')
+pdf_im = plt.imread(pdf_im_path)
+fig2 = plt.figure(figsize = [8.0, 7.5])
+plt.figimage(pdf_im)
+
+plt.show()
diff --git a/lib/matplotlib/mpl-data/sample_data/None_vs_nearest-pdf.png b/lib/matplotlib/mpl-data/sample_data/None_vs_nearest-pdf.png
new file mode 100644
index 000000000000..b8ae896301ec
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diff --git a/lib/matplotlib/mpl-data/sample_data/necked_tensile_specimen.png b/lib/matplotlib/mpl-data/sample_data/necked_tensile_specimen.png
new file mode 100644
index 000000000000..31a2250423ca
Binary files /dev/null and b/lib/matplotlib/mpl-data/sample_data/necked_tensile_specimen.png differ