Jarvis dithering

Also known as Jarvis-Judice-Ninke dithering, JJN dithering

An error-diffusion method that spreads error across a broader neighborhood than Floyd-Steinberg.

In the workflow

Why Jarvis dithering matters

It often creates smooth photographic transitions, but the broader pattern is not automatically best for every size and material.

Practical check

How to evaluate it

Compare Jarvis with Floyd-Steinberg and Stucki using the same source, size, and DPI. Inspect smooth skin or sky transitions alongside fine edges before selecting it for a material test.

See the pixels

Jarvis dithering, shown on the same portrait

Jarvis-Judice-Ninke spreads error across a wider neighborhood than Floyd-Steinberg. The detail crop shows how the same cheek tones become a different arrangement of dots; the gray input has not changed.

01 / Fixed inputGrayscale source
Matching crop of the sample portrait's eyes and cheek before dithering
02 / One-bit outputJarvis
Jarvis output of the same eye and cheek crop, using only black and white pixels

Jarvis: Compare the cheek's midtones with Stucki while keeping the eye and eyebrow edges in view.

Matching 200 × 200-pixel crops, taken after the full images were dithered. Previews fit your screen. Open a downloaded PNG at 100% to inspect the actual pixels.

Computed bitmap examples from EngravePrep's bundled sample portrait. These are not physical engraving results or a material recommendation.

Download the full-size PNGs600 × 750 pixels · 300 DPI metadata · 2 × 2.5 inches at that DPI

A smoother-looking screen preview does not establish a better engraving. Check whether your tested process keeps nearby dots separate before choosing Jarvis for the final piece.

See the complete comparison and how the examples were made.

Go deeper

Compare Stucki, Jarvis, and Floyd-Steinberg with computed one-bit PNG examples, matching detail crops, and practical checks for laser photo preparation.

Read the complete guide