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

    Click :ref:`here <sphx_glr_download_advanced_image_processing_auto_examples_plot_denoising.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_advanced_image_processing_auto_examples_plot_denoising.py:


Denoising an image with the median filter
==========================================

This example shows the original image, the noisy image, the denoised
one (with the median filter) and the difference between the two.




.. image:: /advanced/image_processing/auto_examples/images/sphx_glr_plot_denoising_001.png
    :class: sphx-glr-single-img





.. code-block:: python


    import numpy as np
    from scipy import ndimage
    import matplotlib.pyplot as plt

    im = np.zeros((20, 20))
    im[5:-5, 5:-5] = 1
    im = ndimage.distance_transform_bf(im)
    im_noise = im + 0.2*np.random.randn(*im.shape)

    im_med = ndimage.median_filter(im_noise, 3)

    plt.figure(figsize=(16, 5))

    plt.subplot(141)
    plt.imshow(im, interpolation='nearest')
    plt.axis('off')
    plt.title('Original image', fontsize=20)
    plt.subplot(142)
    plt.imshow(im_noise, interpolation='nearest', vmin=0, vmax=5)
    plt.axis('off')
    plt.title('Noisy image', fontsize=20)
    plt.subplot(143)
    plt.imshow(im_med, interpolation='nearest', vmin=0, vmax=5)
    plt.axis('off')
    plt.title('Median filter', fontsize=20)
    plt.subplot(144)
    plt.imshow(np.abs(im - im_med), cmap=plt.cm.hot, interpolation='nearest')
    plt.axis('off')
    plt.title('Error', fontsize=20)


    plt.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9, bottom=0, left=0,
                        right=1)

    plt.show()

**Total running time of the script:** ( 0 minutes  0.046 seconds)


.. _sphx_glr_download_advanced_image_processing_auto_examples_plot_denoising.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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