Examples
Basic Examples (2)
Apply dithering to an image:
Specify the number of colors per channel:
Scope (3)
Specify a different number of colors per channel for each channel:
See each channel separately:
Specify the quantization error parameter to control how "noisy" the image appears:
Apply directly to an array of data:
Options (4)
PreserveSize (2)
By default, the size of the image will be reduced by 1 on each side:
Set "PreserveSize" to True to ensure the output has the same dimensions:
For very small images, using "PreserveSize"→False can yield better image quality:
ColorsPerChannel (2)
The value of the "ColorsPerChannel" option is equivalent to using the two-argument form:
If the second argument is provided, the option specification is ignored:
Properties and Relations (1)
Use Rasterize to dither arbitrary expressions:
Possible Issues (3)
When giving a list as the second argument, it must have the same length as the number of image channels:
The colorspace of an image can significantly affect the output:
When applying to an array, all values must be numeric:
Neat Examples (4)
Create a "Maze" Image (4)
Start by applying dithering to the grayscale version of an image:
Extract the set of coordinates corresponding to dark pixels with PixelValuePositions and add some slight noise:
Use FindShortestTour to generate a single line that visits very point:
Use the original image to add some color:
Related Links
Version History
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1.0.1
– 12 January 2024
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1.0.0
– 29 May 2019
Related Resources