ants.ops.denoise_image

denoise_image(image, mask=None, shrink_factor=1, p=1, r=2, noise_model='Rician', v=0)[source]

Denoise an image using a spatially adaptive filter originally described in J. V. Manjon, P. Coupe, Luis Marti-Bonmati, D. L. Collins, and M. Robles. Adaptive Non-Local Means Denoising of MR Images With Spatially Varying Noise Levels, Journal of Magnetic Resonance Imaging, 31:192-203, June 2010.

ANTsR function: denoiseImage

Parameters:

  • image (ants.core.ANTsImage) – scalar image to denoise.

  • mask (ants.core.ANTsImage) – to limit the denoise region.

  • shrink_factor (scalar) – downsampling level performed within the algorithm.

  • p (int or character of format '2x2' where the x separates vector entries) – patch radius for local sample.

  • r (int or character of format '2x2' where the x separates vector entries) – search radius from which to choose extra local samples.

  • noise_model (str) – ‘Rician’ or ‘Gaussian’

Return type:

ants.core.ANTsImage

Example

>>> import ants
>>> import numpy as np
>>> image = ants.image_read(ants.get_ants_data('r16'))
>>> # add fairly large salt and pepper noise
>>> imagenoise = image + np.random.randn(*image.shape).astype('float32')*5
>>> imagedenoise = ants.denoise_image(imagenoise, ants.get_mask(image))