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

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

.. _sphx_glr_examples_plot_registration.py:

Image registration
==================

Demonstration of image registration using optical flow.

By definition, the optical flow is the vector field *(u, v)* verifying
*I1(x+u, y+v) = I0(x, y)*. It can then be used for registeration by
image warping.

To display registration results, an RGB image is constructed by
assining the result of the registration to the red channel and the
target image to the green and blue channels. A perfect registration
results in a gray level image while misregistred pixels appear colored
in the constructed RGB image.



.. image:: /examples/images/sphx_glr_plot_registration_001.png
    :class: sphx-glr-single-img





.. code-block:: default


    import numpy as np
    import matplotlib.pyplot as plt
    from skimage.transform import warp

    import pyimof

    # --- Loaf the Urban2 sequence

    I0, I1 = pyimof.data.urban2()

    # --- Estimate the optical flow

    u, v = pyimof.solvers.tvl1(I0, I1)

    # --- Use the estimated optical flow for registeration

    nl, nc = I0.shape

    y, x = np.meshgrid(np.arange(nl), np.arange(nc), indexing='ij')

    wI1 = warp(I1, np.array([y+v, x+u]), mode='nearest')

    # build an RGB image with the unregistered sequence
    seq_im = np.zeros((nl, nc, 3))
    seq_im[..., 0] = I1
    seq_im[..., 1] = I0
    seq_im[..., 2] = I0

    # build an RGB image with the registered sequence
    reg_im = np.zeros((nl, nc, 3))
    reg_im[..., 0] = wI1
    reg_im[..., 1] = I0
    reg_im[..., 2] = I0

    # build an RGB image with the registered sequence
    target_im = np.zeros((nl, nc, 3))
    target_im[..., 0] = I0
    target_im[..., 1] = I0
    target_im[..., 2] = I0

    # --- Show the result

    fig = plt.figure(figsize=(15, 4))
    ax0, ax1, ax2 = fig.subplots(1, 3, True)

    ax0.imshow(seq_im)
    ax0.set_title("Unregistered sequence")
    ax0.set_axis_off()

    ax1.imshow(reg_im)
    ax1.set_title("Registered sequence")
    ax1.set_axis_off()

    ax2.imshow(target_im)
    ax2.set_title("Target")
    ax2.set_axis_off()

    fig.tight_layout()
    plt.show()


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

   **Total running time of the script:** ( 0 minutes  5.138 seconds)


.. _sphx_glr_download_examples_plot_registration.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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