.. 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 19-32

.. code-block:: default


    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 33-37

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 37-41

.. code-block:: default


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








.. GENERATED FROM PYTHON SOURCE LINES 42-43

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

.. GENERATED FROM PYTHON SOURCE LINES 43-55

.. code-block:: default


    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 56-61

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 61-76

.. code-block:: default


    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 77-83

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  2.191 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/v0.21.x?filepath=notebooks/auto_examples/filters/plot_blur_effect.ipynb
        :alt: Launch binder
        :width: 150 px



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

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

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

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


.. only:: html

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

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