Stucki dithering online

About Stucki dithering

Peter Stucki refined the Jarvis–Judice–Ninke kernel in 1981. It uses the same twelve-pixel footprint but with weights that are powers of two, which made it faster on early hardware and nudges more error to the closest neighbours.

The result sits between Floyd–Steinberg and Jarvis: clean, sharp output with smooth tonal transitions. Many people consider Stucki the best-looking error-diffusion algorithm for photographs.

Diffusion kernel

          *   8   4
  2   4   8   4   2
  1   2   4   2   1   (÷42)

“*” marks the current pixel; numbers show how much of its quantization error each neighbour receives.

Best for

• Detailed photographs
• Balanced sharpness and smoothness
• Newspaper / zine style

How to dither an image

1. Add your image. Click Upload image, drag a file onto the preview, or paste with Ctrl/⌘+V. JPG, PNG, WebP and GIF work.
2. Pick an algorithm and palette. Error diffusion (Floyd–Steinberg, Atkinson…) for photos, Bayer for a retro crosshatch.
3. Tune it. Raise pixel size for chunkier pixels; adjust brightness and contrast to control which tones become dark or light.
4. Download. Export a lossless PNG at up to 8× with crisp nearest-neighbour scaling.

FAQ