old_contents: """
  ============
  Thresholding
  ============
  
  Thresholding is used to create a binary image. This example uses Otsu's method
  to calculate the threshold value.
  
  Otsu's method calculates an "optimal" threshold by maximizing the variance
  between the two classes of pixels, which are separated by the threshold.
  Equivalently, the optimal threshold minimizes the intra-class variance.
  
  .. [1] http://en.wikipedia.org/wiki/Otsu's_method
  
  """
  
  import matplotlib.pyplot as plt
  
  from skimage.data import camera
  from skimage.filter import threshold_otsu
  
  
  image = camera()
  thresh = threshold_otsu(image)
  binary = image > thresh
  
  plt.figure(figsize=(10, 3.5))
  plt.subplot(1, 3, 1)
  plt.imshow(image)
  plt.title('original')
  plt.axis('off')
  
  plt.subplot(1, 3, 2)
  plt.hist(image)
  plt.title('histogram')
  plt.axvline(thresh, color='r')
  
  plt.subplot(1, 3, 3)
  plt.imshow(binary)
  plt.title('thresholded')
  plt.axis('off')
  
  plt.show()
  
  
new_contents: """
  ============
  Thresholding
  ============
  
  Thresholding is used to create a binary image. This example uses Otsu's method
  to calculate the threshold value.
  
  Otsu's method calculates an "optimal" threshold (marked by a red line in the
  histogram below) by maximizing the variance between two classes of pixels,
  which are separated by the threshold. Equivalently, this threshold minimizes
  the intra-class variance.
  
  .. [1] http://en.wikipedia.org/wiki/Otsu's_method
  
  """
  
  import matplotlib.pyplot as plt
  
  from skimage.data import camera
  from skimage.filter import threshold_otsu
  
  
  image = camera()
  thresh = threshold_otsu(image)
  binary = image > thresh
  
  plt.figure(figsize=(10, 3.5))
  plt.subplot(1, 3, 1)
  plt.imshow(image)
  plt.title('original')
  plt.axis('off')
  
  plt.subplot(1, 3, 2)
  plt.hist(image)
  plt.title('histogram')
  plt.axvline(thresh, color='r')
  
  plt.subplot(1, 3, 3)
  plt.imshow(binary)
  plt.title('thresholded')
  plt.axis('off')
  
  plt.show()
  
  
subject: emphasize annotation in histogram.