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

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

.. _sphx_glr_generated_examples_io_split-jpeg-to-fits.py:


=====================================================
Convert a 3-color image (JPG) to separate FITS images
=====================================================

This example opens an RGB JPEG image and writes out each channel as a separate
FITS (image) file.

This example uses `pillow <http://python-pillow.org>`_ to read the image,
`matplotlib.pyplot` to display the image, and `astropy.io.fits` to save FITS files.

-------------------

*By: Erik Bray, Adrian Price-Whelan*

*License: BSD*

-------------------




.. code-block:: python


    import numpy as np
    from PIL import Image
    from astropy.io import fits







Set up matplotlib and use a nicer set of plot parameters



.. code-block:: python


    import matplotlib.pyplot as plt
    from astropy.visualization import astropy_mpl_style
    plt.style.use(astropy_mpl_style)







Load and display the original 3-color jpeg image:



.. code-block:: python


    image = Image.open('Hs-2009-14-a-web.jpg')
    xsize, ysize = image.size
    print("Image size: {} x {}".format(xsize, ysize))
    plt.imshow(image)




.. image:: /generated/examples/io/images/sphx_glr_split-jpeg-to-fits_001.png
    :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    Image size: 400 x 232


Split the three channels (RGB) and get the data as Numpy arrays. The arrays
are flattened, so they are 1-dimensional:



.. code-block:: python


    r, g, b = image.split()
    r_data = np.array(r.getdata()) # data is now an array of length ysize*xsize
    g_data = np.array(g.getdata())
    b_data = np.array(b.getdata())
    print(r_data.shape)





.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    (92800,)


Reshape the image arrays to be 2-dimensional:



.. code-block:: python


    r_data = r_data.reshape(ysize, xsize)
    g_data = g_data.reshape(ysize, xsize)
    b_data = b_data.reshape(ysize, xsize)







Write out the channels as separate FITS images



.. code-block:: python


    red = fits.PrimaryHDU(data=r_data)
    red.header['LATOBS'] = "32:11:56" # add spurious header info
    red.header['LONGOBS'] = "110:56"
    red.writeto('red.fits')

    green = fits.PrimaryHDU(data=g_data)
    green.header['LATOBS'] = "32:11:56"
    green.header['LONGOBS'] = "110:56"
    green.writeto('green.fits')

    blue = fits.PrimaryHDU(data=b_data)
    blue.header['LATOBS'] = "32:11:56"
    blue.header['LONGOBS'] = "110:56"
    blue.writeto('blue.fits')







Delete the files created



.. code-block:: python

    import os
    os.remove('red.fits')
    os.remove('green.fits')
    os.remove('blue.fits')






**Total running time of the script:** ( 0 minutes  0.073 seconds)


.. _sphx_glr_download_generated_examples_io_split-jpeg-to-fits.py:


.. only :: html

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



  .. container:: sphx-glr-download

     :download:`Download Python source code: split-jpeg-to-fits.py <split-jpeg-to-fits.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: split-jpeg-to-fits.ipynb <split-jpeg-to-fits.ipynb>`


.. only:: html

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

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