- This repository has been replaced by 'pyvsnr' in: https://github.com/CEA-MetroCarac/pyvnsr

VSNR (Variational Stationary Noise Remover) algorithm in python

This repository contains the python sources of the 2D-GPU based denoising code of the VSNR algorithm issued from the CUDA implementation given in https://github.com/pierre-weiss/VSNR_2D-3D_GPU.

It completes the 2D-CPU/GPU port from MATLAB to python realized in https://github.com/patquem/pyvsnr

$ pip install git+https://github.com/CEA-MetroCarac/pyVSNR.git

In case of problem during CUDA execution (typically 'access memory error'), it may be necessary to recompile the .dll. See the README.txt file for more details.

• numpy
• matplotlib, skimage (for examples and tests execution only)

from pyVSNR import vsnr2d
from skimage import io

# read the image to correct
img = io.imread('image.tif')

# filters definition (Gabor and Dirac filters combination)
filter1 = {'name':'Gabor', 'noise_level':20, 'sigma':(3, 40), 'theta':210}
filter2 = {'name':'Dirac', 'noise_level':10}
filters = [filter1, filter2]

# image processing
img_corr = vsnr2d(img, filters, nite=20, nblocks='auto')

...

For more details concerning usage and parameters, refer to the Pierre Weiss website.

Some applicative examples are given in examples.py. Operating mode and results are reproduced hereafter.

Gaussian noise removal example :

from pyVSNR.examples import ex_camera_gaussian_noise 
ex_camera_gaussian_noise() 

Stripes removal example :

from pyVSNR.examples import ex_camera_stripes 
ex_camera_stripes()

Curtains removal example :

from pyVSNR.examples import ex_camera_curtains 
ex_camera_curtains()

Curtains removal example on real image (FIB-SEM) :

from pyVSNR.examples import ex_fib_sem
ex_fib_sem(show_plot=True)

This is a port to python of the original code developed by Jean EYMERIE and Pierre WEISS.

All credit goes to the original authors.

In case you use the results of this code with your article, please don't forget to cite:

• Fehrenbach, Jérôme, Pierre Weiss, and Corinne Lorenzo. "Variational algorithms to remove stationary noise: applications to microscopy imaging." IEEE Transactions on Image Processing 21.10 (2012): 4420-4430.
• Fehrenbach, Jérôme, and Pierre Weiss. "Processing stationary noise: model and parameter selection in variational methods." SIAM Journal on Imaging Sciences 7.2 (2014): 613-640.
• Escande, Paul, Pierre Weiss, and Wenxing Zhang. "A variational model for multiplicative structured noise removal." Journal of Mathematical Imaging and Vision 57.1 (2017): 43-55.