Filter image¶
Some of the docstrings for this module have been extracted from the scikit-image library and are covered by their respective licenses.
-
class
node_general_filters.
GeneralImageFiltering
[source]¶ Applies simple filtering or scaling algorithms on an image. For more complex operations see the more specialized image manipulation nodes
Algorithms: abs
Computes absolute value or complex magnitude of image
angle
Gives the phase angle of a complex image
center image
Shifts image so that center of mass lies in center of image
clamp
Restricts the output values to a given maximum/minimum
- minimum:
The minimum output value that can be passed through
- maximum:
The maximum output value that can be passed through
-
Two-dimensional Gaussian filter
- sigma-x:
Standard deviation of gaussian filter along X-axis
- sigma-y:
Standard deviation of gaussian filter along Y-axis
- border mode:
Determines how the array borders are handled
- k:
Value outside image borders when method constant is used.
-
Computes an approximation of the determinant of the hessian matrix for each pixel.
- sigma:
Standard deviation of gaussian kernel (default 3.0) used for calculating Hessian.
Approximation is not reliable for sigma < 3.0
imag
Gives the imaginary part of a complex image
-
Creates the integral image of the input.
An integral image contains at coordinate (m,n) the sum of all values above and to the left of it.
S(m,n) = sum(im[0:m, 0:n])
normalize
Adds a (positive) scale and offset so that smallest/highest value in image becomes 0 and 1 respectively.
Operates on each channel separately
- minimum:
Minimum value after normalization
- maximum:
Maximum value after normalization
real
Gives the real valued part of a complex image
scale/offset
Adds a scale and/or an offset to each channel equally
- scale:
Scale factor applied to image before offset
- offset:
Offset applied to image after scale
to integer
Converts all channels into integer data
Inputs: source : image
source image to filter
Outputs: result : image
result after filtering