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What is Image Dithering?

Image dithering arranges patterned or randomized pixel variations to approximate colors or tones unavailable in a limited palette. At normal viewing distance, adjacent pixels can create the perception of an intermediate value.

How Image Dithering works

Dithering controls quantization error by distributing it as visible spatial variation instead of allowing it to form broad contour bands. Ordered matrices create repeatable patterns, error-diffusion filters pass residual error to later pixels, and stochastic methods trade structure for noise-like grain. It is applied while reducing palette size or bit depth, after the target color space is known. The chosen pattern affects both apparent smoothness and the behavior of downstream lossless or lossy encoders.

Key facts

  1. Error diffusion is scan-order dependent: changing traversal direction or processing tiles independently can produce seams and a different pixel pattern.
  2. Ordered dithering uses a fixed threshold matrix, making its texture predictable and often easier to parallelize than algorithms that propagate error between pixels.
  3. Dither does not restore missing color precision; later resizing or recompression can average or rearrange its dots and reveal banding that the original pattern concealed.

When Image Dithering matters

Enable dithering when reducing color depth would otherwise create visible bands or abrupt color transitions. It can improve perceived gradients but may add grain, reduce compressibility, or look distracting in flat regions.

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