Image.decimate#

Image.decimate(m: int = 2, sigma: float | None = None) → Self[source]#

Decimate an image

Parameters:

  • m (int) – decimation factor

  • sigma (float, optional) – standard deviation for Gaussian kernel smoothing, defaults to None

Raises:

ValueError – decimation factor m must be an integer

Returns:

decimated image

Return type:

Image

Return a decimated version of the image whose size is reduced by subsampling every m (an integer) pixels in both dimensions.

The image is smoothed with a Gaussian kernel with standard deviation sigma. If

  • sigma is None then a value of m/2 is used,

  • sigma is zero then no smoothing is performed.

Note

  • If the image has multiple planes, each plane is decimated.

  • Smoothing is applied to the image _before_ decimation to reduce high-spatial-frequency components and hence reduce aliasing artifacts. The standard deviation should be chosen as a function of the maximum spatial-frequency in the image.

Example:

>>> from machinevisiontoolbox import Image
>>> img = Image.Random(size=6)
>>> img.print()
   232  53  93  36   8 220
    85  48   0  65 131  35
     3 141  22 129 212  78
    39  37  10 187 251  49
   206 191 198   9  24 250
    24  50 190 160  46 201
>>> img.decimate(2, sigma=0).print()
   232  93   8
     3  22 212
   206 198  24
References:
Seealso:

replicate scale