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based on an earlier version of the Wolfram Language.
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GradientFilter

GradientFilter[image, r]
gives an image corresponding to the magnitude of the gradient of image, computed using discrete derivatives of a Gaussian of pixel radius r.
GradientFilter[image, {r, Sigma}]
uses a Gaussian with standard deviation Sigma.
GradientFilter[image, {{r1, r2}, ...}]
uses a Gaussian with radii ri etc. in vertical and horizontal directions.
GradientFilter[data, ...]
applies gradient filtering to an array of data.
  • In GradientFilter[data, ...], data can be an array of any rank, and can contain symbolic as well as numerical entries.
Gradient filtering of a multi-channel image:
Adjusted gradient filter of a grayscale image:
Apply gradient filtering to a vector of numbers:
Gradient filtering of a multi-channel image:
In[1]:=
Click for copyable input
Out[1]=
 
Adjusted gradient filter of a grayscale image:
In[1]:=
Click for copyable input
Out[1]=
 
Apply gradient filtering to a vector of numbers:
In[1]:=
Click for copyable input
Out[1]=
Use gradient filtering to find edges:
Create a random texture from uniform noise:
New in 7