ENH: Histogram equalization

ants/utils/__init__.py

@@ -17,6 +17,7 @@
 from .get_neighborhood import (get_neighborhood_in_mask,
             get_neighborhood_at_voxel)
 from .histogram_match_image import histogram_match_image
+from .histogram_equalize_image import histogram_equalize_image
 from .hausdorff_distance import hausdorff_distance
 from .image_similarity import image_similarity
 from .image_to_cluster_images import image_to_cluster_images

ants/utils/histogram_equalize_image.py

@@ -0,0 +1,38 @@
+__all__ = ['histogram_equalize_image']
+
+import numpy as np
+
+from .. import core
+
+def histogram_equalize_image(image, number_of_histogram_bins=256):
+    """
+    Histogram equalize image
+
+    # from http://www.janeriksolem.net/histogram-equalization-with-python-and.html      
+
+    Arguments
+    ---------
+    image : ANTsImage
+        source image
+
+    number_of_histogram_bins : integer
+        number of bins for cumulative histogram
+
+    Example
+    -------
+    >>> import ants
+    >>> src_img = ants.image_read(ants.get_data('r16'))
+    >>> src_img_eq = ants.histogram_equalize_image(src_img)
+    """
+
+    image_array = image.numpy()
+    image_histogram, bins = np.histogram(image_array.flatten(), number_of_histogram_bins, density=True)
+    cdf = image_histogram.cumsum()
+    cdf = (number_of_histogram_bins-1) * cdf / cdf[-1]
+    image_array_equalized_flat = np.interp(image_array.flatten(), bins[:-1], cdf)
+    image_array_equalized = image_array_equalized_flat.reshape(image_array.shape)    
+    image_equalized = core.from_numpy(image_array_equalized)
+
+    return core.copy_image_info(image, image_equalized)
+
+