Merge pull request #1291 from jni/exposure-fix

Set float histograms bins between 0 and 1

skimage/exposure/exposure.py

@@ -84,7 +84,7 @@ def histogram(image, nbins=256):
         idx = np.nonzero(hist)[0][0]
         return hist[idx:], bin_centers[idx:]
     else:
-        hist, bin_edges = np.histogram(image.flat, nbins)
+        hist, bin_edges = np.histogram(image.flat, bins=nbins)
         bin_centers = (bin_edges[:-1] + bin_edges[1:]) / 2.
         return hist, bin_centers
 
@@ -136,8 +136,10 @@ def equalize_hist(image, nbins=256, mask=None):
     ----------
     image : array
         Image array.
-    nbins : int
-        Number of bins for image histogram.
+    nbins : int, optional
+        Number of bins for image histogram. Note: this argument is
+        ignored for integer images, for which each integer is its own
+        bin.
     mask: ndarray of bools or 0s and 1s, optional
         Array of same shape as `image`. Only points at which mask == True
         are used for the equalization, which is applied to the whole image.
@@ -157,7 +159,6 @@ def equalize_hist(image, nbins=256, mask=None):
     .. [2] http://en.wikipedia.org/wiki/Histogram_equalization
 
     """
-    image = img_as_float(image)
     if mask is not None:
         mask = np.array(mask, dtype=bool)
         cdf, bin_centers = cumulative_distribution(image[mask], nbins)

skimage/exposure/tests/test_exposure.py

@@ -2,7 +2,8 @@ import warnings
 
 import numpy as np
 from numpy.testing import assert_array_almost_equal as assert_close
-from numpy.testing import assert_array_equal, assert_raises
+from numpy.testing import (assert_array_equal, assert_raises,
+                           assert_almost_equal)
 
 import skimage
 from skimage import data
@@ -38,10 +39,17 @@ def test_all_negative_image():
 
 np.random.seed(0)
 
+test_img_int = data.camera()
 # squeeze image intensities to lower image contrast
-test_img = skimage.img_as_float(data.camera())
+test_img = skimage.img_as_float(test_img_int)
 test_img = exposure.rescale_intensity(test_img / 5. + 100)
 
+def test_equalize_uint8_approx():
+    """Check integer bins used for uint8 images."""
+    img_eq0 = exposure.equalize_hist(test_img_int)
+    img_eq1 = exposure.equalize_hist(test_img_int, nbins=3)
+    np.testing.assert_allclose(img_eq0, img_eq1)
+
 
 def test_equalize_ubyte():
     img = skimage.img_as_ubyte(test_img)