Here I implemented in R some dithering algorithms:

– Floyd-Steinberg dithering

– Bill Atkinson dithering

– Jarvis-Judice-Ninke dithering

– Sierra 2-4a dithering

– Stucki dithering

– Burkes dithering

– Sierra2 dithering

– Sierra3 dithering

For each algorithm, I wrote a 2-dimensional convolution function (a matrix passing over a matrix); it is slow because I didn’t implemented any fasting tricks. It can be easily implemented in C, then used in R for a faster solution.

Then, a function to transform a grey image in a grey-dithered image is provided, with an example. The library rimage was used for loading and displaying images (see the other post R is a cool image editor).

These function can be easily re-coded for a RGB image.

Only the first code is commented, ’cause they’re all very similar.

library(rimage)

y <- read.jpeg("valve.jpg")

plot(y)

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Floyd-Steinberg dithering

plot(normalize(grey2FSdith(rgb2grey(y))))

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Bill Atkinson dithering

plot(normalize(grey2ATKdith(rgb2grey(y))))

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Jarvis-Judice-Ninke dithering

plot(normalize(grey2JJNdith(rgb2grey(y))))

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Sierra 2-4a dithering filter

plot(normalize(grey2S24adith(rgb2grey(y))))

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Stucki dithering

plot(normalize(grey2Stucki(rgb2grey(y))))

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Burkes dithering

plot(normalize(grey2Burkes(rgb2grey(y))))

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Sierra2 dithering

plot(normalize(grey2Sierra2(rgb2grey(y))))

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Sierra3 dithering

plot(normalize(grey2Sierra3(rgb2grey(y))))