Import Dependencies¶

Import functions from PySAP and ModOpt.

import numpy as np
from pysap import Image
from pysap.data import get_sample_data
from pysap.plugins.astro.deconvolution.deconvolve import sparse_deconv_condatvu
from modopt.signal.noise import add_noise
from modopt.math.convolve import convolve

Load astro data¶

Load the example images

galaxy = get_sample_data('astro-galaxy')
psf = get_sample_data('astro-psf')

Show the clean galaxy image

# galaxy.show()

Generate noisy observation¶

Convolve the image with a point spread function (PSF) using the convolve function. Then add random Gaussian noise with standard deviation 0.0005 using the add_noise function.

obs_data = add_noise(convolve(galaxy.data, psf.data), sigma=0.0005)

Create a PySAP image object

image_obs = Image(data=np.abs(obs_data))

Show the noisy galaxy image

# image_obs.show()

Deconvolve¶

Use the sparse_deconv_condatvu function to deconvolve the noisy image and set the maximum number of iterations to 3000.

deconv_data = sparse_deconv_condatvu(obs_data, psf.data, n_iter=3000)

Create a PySAP image object for the result

image_rec = Image(data=np.abs(deconv_data))

Show the deconvolved galaxy image

# image_rec.show()

Residual¶

Create a PySAP image object for the residual

residual = Image(data=np.abs(galaxy.data - deconv_data))

Show the residual

# residual.show()

Total running time of the script: ( 0 minutes 0.000 seconds)

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