downscale-local-mean

downscale_local_mean

skimage.transform.downscale_local_mean(image, factors, cval=0, clip=True) [source]

Down-sample N-dimensional image by local averaging.

The image is padded with cval if it is not perfectly divisible by the integer factors.

In contrast to the 2-D interpolation in skimage.transform.resize and skimage.transform.rescale this function may be applied to N-dimensional images and calculates the local mean of elements in each block of size factors in the input image.

Parameters:

image : ndarray

N-dimensional input image.

factors : array_like

Array containing down-sampling integer factor along each axis.

cval : float, optional

Constant padding value if image is not perfectly divisible by the integer factors.

Returns:

image : ndarray

Down-sampled image with same number of dimensions as input image.

Examples

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>>> a = np.arange(15).reshape(3, 5)
>>> a
array([[ 01234],
       [ 56789],
       [10, 11, 12, 13, 14]])
>>> downscale_local_mean(a, (2, 3))
array([[ 3.54. ],
       [ 5.54.5]])
doc_scikit_image
2025-01-10 15:47:30
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