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bundles / skimage 0.26.1rc0.dev0+git20260530.b607368ff / skimage / transform / _warps / rescale

function

skimage.transform._warps:rescale

source: /dev/scikit-image/src/skimage/transform/_warps.py :228

Signature

def   rescale ( image ,  scale ,  order = None ,  mode = reflect ,  cval = 0 ,  clip = True ,  preserve_range = False ,  anti_aliasing = None ,  anti_aliasing_sigma = None ,  * ,  channel_axis = None )

Summary

Scale image by a certain factor.

Extended Summary

Performs interpolation to up-scale or down-scale N-dimensional images. Note that anti-aliasing should be enabled when down-sizing images to avoid aliasing artifacts. For down-sampling with an integer factor also see skimage.transform.downscale_local_mean.

Parameters

image : (M, N[, ...][, C]) ndarray

Input image.

scale : {float, tuple of floats}

Scale factors for spatial dimensions. Separate scale factors can be defined as (m, n[, ...]).

Returns

scaled : ndarray

Scaled version of the input.

Other Parameters

order : int, optional

The order of the spline interpolation, default is 0 if image.dtype is bool and 1 otherwise. The order has to be in the range 0-5. See skimage.transform.warp for detail.

mode : {'constant', 'edge', 'symmetric', 'reflect', 'wrap'}, optional

Points outside the boundaries of the input are filled according to the given mode. Modes match the behaviour of numpy.pad.

cval : float, optional

Used in conjunction with mode 'constant', the value outside the image boundaries.

clip : bool, optional

Whether to clip the output to the range of values of the input image. This is enabled by default, since higher order interpolation may produce values outside the given input range.

preserve_range : bool, optional

Whether to keep the original range of values. Otherwise, the input image is converted according to the conventions of img_as_float. Also see https://scikit-image.org/docs/dev/user_guide/data_types.html

anti_aliasing : bool, optional

Whether to apply a Gaussian filter to smooth the image prior to down-scaling. It is crucial to filter when down-sampling the image to avoid aliasing artifacts. If input image data type is bool, no anti-aliasing is applied.

anti_aliasing_sigma : {float, tuple of floats}, optional

Standard deviation for Gaussian filtering to avoid aliasing artifacts. By default, this value is chosen as (s - 1) / 2 where s is the down-scaling factor.

channel_axis : int or None, optional

If None, the image is assumed to be a grayscale (single channel) image. Otherwise, this parameter indicates which axis of the array corresponds to channels.

Notes

Modes 'reflect' and 'symmetric' are similar, but differ in whether the edge pixels are duplicated during the reflection. As an example, if an array has values [0, 1, 2] and was padded to the right by four values using symmetric, the result would be [0, 1, 2, 2, 1, 0, 0], while for reflect it would be [0, 1, 2, 1, 0, 1, 2].

Examples

from skimage import data
from skimage.transform import rescale
image = data.camera()
rescale(image, 0.1).shape
rescale(image, 0.5).shape
✓

Aliases

  • skimage.transform.rescale

Referenced by

This package