Image.LUT#

Image.LUT(lut: Any, colororder: str | dict[str, Any] | None = None) → Image[source]#

Apply lookup table

Parameters:

lut (array_like(256), ndarray(256,N)) – lookup table
colororder (str or dict) – colororder for output image, optional

Returns:

transformed image

Return type:

Image

For a greyscale image the LUT can be:

(256,)

(256,N) in which case the resulting image has N planes created by applying the I’th column of the LUT to the input image

For a color image the LUT can be:

(256,) and applied to every plane, or

(256,N) where the LUT columns are applied to the N planes of the input image.

Example:

>>> from machinevisiontoolbox import Image
>>> import numpy as np
>>> img = Image([[100, 150], [200, 250]])
>>> img.LUT(np.arange(255, -1, -1, dtype='uint8')).A
array([[155, 105],
       [ 55,   5]], dtype=uint8)

Note

Works only for uint8 and int8 image and LUT.

References:

P. Corke, Robotics, Vision & Control for Python, Springer, 2023, Section 11.3.

Important

Uses OpenCV function cv2.LUT which accepts multiple-channel, CV_8U images.

Seealso:: cv2.LUT