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.

7.5.18. 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, non-finite values in input image are replaced by zeros.

imgs: Niimg-like object or iterable of Niimg-like objects

See Image(s) to smooth.

fwhm: scalar, numpy.ndarray, ‘fast’ or None

Smoothing strength, as a Full-Width 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 non-finite values is needed).

In corner case situations, fwhm is simply kept to None when fwhm is specified as fwhm=0.

filtered_img: nibabel.Nifti1Image or list of.

Input image, filtered. If imgs is an iterable, then filtered_img is a list.