.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/color_exposure/plot_equalize.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_color_exposure_plot_equalize.py>`
        to download the full example code or to run this example in your browser via Binder

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_color_exposure_plot_equalize.py:


======================
Histogram Equalization
======================

This examples enhances an image with low contrast, using a method called
*histogram equalization*, which "spreads out the most frequent intensity
values" in an image [1]_. The equalized image has a roughly linear cumulative
distribution function.

While histogram equalization has the advantage that it requires no parameters,
it sometimes yields unnatural looking images.  An alternative method is
*contrast stretching*, where the image is rescaled to include all intensities
that fall within the 2nd and 98th percentiles [2]_.

.. [1] https://en.wikipedia.org/wiki/Histogram_equalization
.. [2] http://homepages.inf.ed.ac.uk/rbf/HIPR2/stretch.htm

.. GENERATED FROM PYTHON SOURCE LINES 20-101



.. image-sg:: /auto_examples/color_exposure/images/sphx_glr_plot_equalize_001.png
   :alt: Low contrast image, Contrast stretching, Histogram equalization, Adaptive equalization
   :srcset: /auto_examples/color_exposure/images/sphx_glr_plot_equalize_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib
    import matplotlib.pyplot as plt
    import numpy as np

    from skimage import data, img_as_float
    from skimage import exposure


    matplotlib.rcParams['font.size'] = 8


    def plot_img_and_hist(image, axes, bins=256):
        """Plot an image along with its histogram and cumulative histogram."""
        image = img_as_float(image)
        ax_img, ax_hist = axes
        ax_cdf = ax_hist.twinx()

        # Display image
        ax_img.imshow(image, cmap=plt.cm.gray)
        ax_img.set_axis_off()

        # Display histogram
        ax_hist.hist(image.ravel(), bins=bins, histtype='step', color='black')
        ax_hist.ticklabel_format(axis='y', style='scientific', scilimits=(0, 0))
        ax_hist.set_xlabel('Pixel intensity')
        ax_hist.set_xlim(0, 1)
        ax_hist.set_yticks([])

        # Display cumulative distribution
        img_cdf, bins = exposure.cumulative_distribution(image, bins)
        ax_cdf.plot(bins, img_cdf, 'r')
        ax_cdf.set_yticks([])

        return ax_img, ax_hist, ax_cdf


    # Load an example image
    img = data.moon()

    # Contrast stretching
    p2, p98 = np.percentile(img, (2, 98))
    img_rescale = exposure.rescale_intensity(img, in_range=(p2, p98))

    # Equalization
    img_eq = exposure.equalize_hist(img)

    # Adaptive Equalization
    img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)

    # Display results
    fig = plt.figure(figsize=(8, 5))
    axes = np.zeros((2, 4), dtype=object)
    axes[0, 0] = fig.add_subplot(2, 4, 1)
    for i in range(1, 4):
        axes[0, i] = fig.add_subplot(2, 4, 1 + i, sharex=axes[0, 0], sharey=axes[0, 0])
    for i in range(0, 4):
        axes[1, i] = fig.add_subplot(2, 4, 5 + i)

    ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0])
    ax_img.set_title('Low contrast image')

    y_min, y_max = ax_hist.get_ylim()
    ax_hist.set_ylabel('Number of pixels')
    ax_hist.set_yticks(np.linspace(0, y_max, 5))

    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('Histogram equalization')

    ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_adapteq, axes[:, 3])
    ax_img.set_title('Adaptive equalization')

    ax_cdf.set_ylabel('Fraction of total intensity')
    ax_cdf.set_yticks(np.linspace(0, 1, 5))

    # prevent overlap of y-axis labels
    fig.tight_layout()
    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.773 seconds)


.. _sphx_glr_download_auto_examples_color_exposure_plot_equalize.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/scikit-image/scikit-image/v0.23.1?filepath=notebooks/auto_examples/color_exposure/plot_equalize.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_equalize.ipynb <plot_equalize.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_equalize.py <plot_equalize.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_