Note
This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
nilearn.image.smooth_img¶

nilearn.image.
smooth_img
(imgs, fwhm)¶ Smooth images by applying a Gaussian filter.
Apply a Gaussian filter along the three first dimensions of arr. In all cases, nonfinite values in input image are replaced by zeros.
Parameters: imgs: Niimglike object or iterable of Niimglike objects :
See http://nilearn.github.io/building_blocks/manipulating_mr_images.html#niimg. Image(s) to smooth.
fwhm: scalar, numpy.ndarray, ‘fast’ or None :
Smoothing strength, as a FullWidth at Half Maximum, in millimeters. If a scalar is given, width is identical on all three directions. A numpy.ndarray must have 3 elements, giving the FWHM along each axis. If fwhm == ‘fast’, a fast smoothing will be performed with a filter [0.2, 1, 0.2] in each direction and a normalisation to preserve the scale. If fwhm is None, no filtering is performed (useful when just removal of nonfinite values is needed)
Returns: filtered_img: nibabel.Nifti1Image or list of. :
Input image, filtered. If imgs is an iterable, then filtered_img is a list.