07-27, 14:40–14:50 (UTC), Blue
Dithering algorithms are a group of color quantization techniques that create the illusion of continuous color in images with small color palettes by adding high-frequency noise or patterns. Traditionally used in printing, they are now mostly used for stylistic purposes.
DitherPunk.jl implements a wide variety of fast and extensible dithering algorithms. Using its example, I will demonstrate how packages for creative coding can be built on top of the JuliaImages ecosystem.
In this talk I will present DitherPunk.jl, a Julia package implementing over 30 dithering algorithms: from ordered dithering with Bayer matrices to digital halftoning and error diffusion methods such as Floyd-Steinberg.
DitherPunk.jl can be used for binary dithering, channel-wise dithering and for dithering with custom color palettes.
Typically, color dithering algorithms are implemented using Euclidean distances in RGB color space. By building on top of packages from the JuliaImages ecosystem such as Colors.jl and ColorVectorSpace.jl, algorithms can be applied in any color space using any color distance metric, allowing for a lot of creative experimentation.
Due to its modular design, DitherPunk.jl is highly extensible. This will be demonstrated by creating an ordered dithering algorithm from a signed distance function.
Adrian Hill is a PhD student in the Machine Learning Group at TU Berlin.