PPP (with BM3D) Image Deconvolution (APGM Solver)¶

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install 'scico[examples] @ git+https://github.com/lanl/scico'

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install 'scico[examples] @ git+https://github.com/lanl/scico
'
# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install git+https://github.com/lanl/scico
!pip install xdesign

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install git+https://github.com/lanl/scico
!pip install xdesign

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install git+https://github.com/lanl/scico
!pip install xdesign

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install git+https://github.com/lanl/scico
!pip install xdesign

# This scico project Jupyter notebook has been automatically modified
# to install the dependencies required for running it on Google Colab.
# If you encounter any problems in running it, please open an issue at
#   https://github.com/lanl/scico-data/issues

!pip install git+https://github.com/lanl/scico
!pip install xdesign

import numpy as np

import jax

from xdesign import Foam, discrete_phantom

import scico.numpy as snp
from scico import functional, linop, loss, metric, plot, random
from scico.optimize.pgm import AcceleratedPGM
from scico.util import device_info
plot.config_notebook_plotting()

np.random.seed(1234)
N = 512  # image size
x_gt = discrete_phantom(Foam(size_range=[0.075, 0.0025], gap=1e-3, porosity=1), size=N)
x_gt = jax.device_put(x_gt)  # convert to jax array, push to GPU

n = 5  # convolution kernel size
σ = 20.0 / 255  # noise level

psf = snp.ones((n, n)) / (n * n)
A = linop.Convolve(h=psf, input_shape=x_gt.shape)

Ax = A(x_gt)  # blurred image
noise, key = random.randn(Ax.shape)
y = Ax + σ * noise

f = loss.SquaredL2Loss(y=y, A=A)

L0 = 15  # APGM inverse step size parameter
λ = L0 * 2.0 / 255  # BM3D regularization strength
g = λ * functional.BM3D()

maxiter = 50  # number of APGM iterations

solver = AcceleratedPGM(
    f=f, g=g, L0=L0, x0=A.T @ y, maxiter=maxiter, itstat_options={"display": True, "period": 10}
)