.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/filters/plot_blur_effect.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_filters_plot_blur_effect.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_filters_plot_blur_effect.py:


=========================
Estimate strength of blur
=========================

This example shows how the metric implemented in ``measure.blur_effect``
behaves, both as a function of the strength of blur and of the size of the
re-blurring filter. This no-reference perceptual blur metric is described in
[1]_.

.. [1] Frederique Crete, Thierry Dolmiere, Patricia Ladret, and Marina
   Nicolas "The blur effect: perception and estimation with a new
   no-reference perceptual blur metric" Proc. SPIE 6492, Human Vision and
   Electronic Imaging XII, 64920I (2007)
   https://hal.archives-ouvertes.fr/hal-00232709
   :DOI:`10.1117/12.702790`

.. GENERATED FROM PYTHON SOURCE LINES 19-30

.. code-block:: Python


    import matplotlib.pyplot as plt
    import numpy as np
    import pandas as pd
    import scipy.ndimage as ndi

    import plotly
    import plotly.express as px
    from skimage import color, data, measure









.. GENERATED FROM PYTHON SOURCE LINES 31-35

Generate series of increasingly blurred images
==============================================
Let us load an image available through scikit-image’s data registry. The
blur metric applies to single-channel images.

.. GENERATED FROM PYTHON SOURCE LINES 35-39

.. code-block:: Python


    image = data.astronaut()
    image = color.rgb2gray(image)








.. GENERATED FROM PYTHON SOURCE LINES 40-41

Let us blur this image with a series of uniform filters of increasing size.

.. GENERATED FROM PYTHON SOURCE LINES 41-53

.. code-block:: Python


    blurred_images = [ndi.uniform_filter(image, size=k) for k in range(2, 32, 2)]
    img_stack = np.stack(blurred_images)

    fig = px.imshow(
        img_stack,
        animation_frame=0,
        binary_string=True,
        labels={'animation_frame': 'blur strength ~'},
    )
    plotly.io.show(fig)




.. raw:: html
    :file: images/sphx_glr_plot_blur_effect_001.html





.. GENERATED FROM PYTHON SOURCE LINES 54-59

Plot blur metric
================
Let us compute the blur metric for all blurred images: We expect it to
increase towards 1 with increasing blur strength. We compute it for three
different values of re-blurring filter: 3, 11 (default), and 30.

.. GENERATED FROM PYTHON SOURCE LINES 59-75

.. code-block:: Python


    B = pd.DataFrame(
        data=np.zeros((len(blurred_images), 3)),
        columns=['h_size = 3', 'h_size = 11', 'h_size = 30'],
    )
    for ind, im in enumerate(blurred_images):
        B.loc[ind, 'h_size = 3'] = measure.blur_effect(im, h_size=3)
        B.loc[ind, 'h_size = 11'] = measure.blur_effect(im, h_size=11)
        B.loc[ind, 'h_size = 30'] = measure.blur_effect(im, h_size=30)

    B.plot().set(
        xlabel='blur strength (half the size of uniform filter)', ylabel='blur metric'
    )

    plt.show()




.. image-sg:: /auto_examples/filters/images/sphx_glr_plot_blur_effect_002.png
   :alt: plot blur effect
   :srcset: /auto_examples/filters/images/sphx_glr_plot_blur_effect_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 76-82

We can see that as soon as the blur is stronger than (reaches the scale of)
the size of the uniform filter, the metric gets close to 1 and, hence, tends
asymptotically to 1 with increasing blur strength.
The value of 11 pixels gives a blur metric which correlates best with human
perception. That's why it's the default value in the implementation of the
perceptual blur metric ``measure.blur_effect``.


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

   **Total running time of the script:** (0 minutes 1.628 seconds)


.. _sphx_glr_download_auto_examples_filters_plot_blur_effect.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/v0.23.2?filepath=notebooks/auto_examples/filters/plot_blur_effect.ipynb
        :alt: Launch binder
        :width: 150 px

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

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

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

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


.. only:: html

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

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