add examples - to be cont.

doc/examples/plot_local_equalize.py

@@ -0,0 +1,86 @@
+"""
+===============================
+Local Histogram Equalization
+===============================
+
+This examples enhances an image with low contrast, using a method called
+*local histogram equalization*, which "spreads out the most frequent intensity
+values" in an image . The equalized image has a roughly linear cumulative
+distribution function for each pixel neigborhood.
+
+to be adjusted...
+
+.. [1] http://en.wikipedia.org/wiki/Histogram_equalization
+.. [2] http://homepages.inf.ed.ac.uk/rbf/HIPR2/stretch.htm
+
+"""
+
+from skimage import data
+from skimage.util.dtype import dtype_range
+from skimage import exposure
+from skimage.rank import egalise
+from skimage.morphology import disk
+
+
+import matplotlib.pyplot as plt
+
+import numpy as np
+
+def plot_img_and_hist(img, axes, bins=256):
+    """Plot an image along with its histogram and cumulative histogram.
+
+    """
+    ax_img, ax_hist = axes
+    ax_cdf = ax_hist.twinx()
+
+    # Display image
+    ax_img.imshow(img, cmap=plt.cm.gray)
+    ax_img.set_axis_off()
+
+    # Display histogram
+    ax_hist.hist(img.ravel(), bins=bins)
+    ax_hist.ticklabel_format(axis='y', style='scientific', scilimits=(0, 0))
+    ax_hist.set_xlabel('Pixel intensity')
+
+    xmin, xmax = dtype_range[img.dtype.type]
+    ax_hist.set_xlim(xmin, xmax)
+
+    # Display cumulative distribution
+    img_cdf, bins = exposure.cumulative_distribution(img, bins)
+    ax_cdf.plot(bins, img_cdf, 'r')
+
+    return ax_img, ax_hist, ax_cdf
+
+
+# Load an example image
+img = data.moon()
+
+# Contrast stretching
+p2 = np.percentile(img, 2)
+p98 = np.percentile(img, 98)
+img_rescale = exposure.rescale_intensity(img, in_range=(p2, p98))
+
+# Equalization
+selem = disk(30)
+img_eq = egalise(img,selem=selem)
+
+
+# Display results
+f, axes = plt.subplots(2, 3, figsize=(8, 4))
+
+ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0])
+ax_img.set_title('Low contrast image')
+ax_hist.set_ylabel('Number of pixels')
+
+ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_rescale, axes[:, 1])
+ax_img.set_title('Contrast stretching')
+
+ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_eq, axes[:, 2])
+ax_img.set_title('Local Histogram equalization')
+ax_cdf.set_ylabel('Fraction of total intensity')
+
+
+# prevent overlap of y-axis labels
+plt.subplots_adjust(wspace=0.4)
+plt.show()
+