Effects / Dither

Jarvis-Judice-Ninke Dither

The Jarvis-Judice-Ninke algorithm is a high-quality error diffusion dithering method that distributes quantization error across a 3-row, 5-column neighborhood. It produces smoother gradients than simpler algorithms at the cost of more processing.

dither-jarvis-judice-ninkePro

Effect ID: dither-jarvis-judice-ninke

Example Configuration

jarvis-judice-ninke.json

{
  "effectId": "dither-jarvis-judice-ninke",
  "dither": {
    "pattern": "jarvisJudiceNinke",
    "pixelation": 4,
    "paletteId": "monochrome",
    "colors": ["#000000", "#ffffff"],
    "brightness": 1,
    "contrast": 1,
    "threshold": 0.5
  }
}

Error Diffusion Matrix

The Jarvis-Judice-Ninke matrix distributes error over 12 neighboring pixels:

          *   7   5      (row 0: current row)
  3   5   7   5   3      (row 1: next row)
  1   3   5   3   1      (row 2: two rows down)

  Divisor: 48

Characteristics

Smooth gradients - Large diffusion area produces smoother results
Reduced artifacts - Less visible patterns than Floyd-Steinberg
Higher quality - Better tonal reproduction for photographs
More computation - Processes 12 pixels per sample

Comparison with Other Algorithms

vs Floyd-Steinberg - Smoother but slower processing
vs Atkinson - Higher quality but less stylized look
vs Stucki - Similar quality, slight differences in grain

Tips

Best for photographs requiring smooth tonal transitions
Use with higher color counts for subtle color reduction
Excellent for print preparation where quality matters
Consider Atkinson if you want more visible texture