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What is Unsharp Masking?

Unsharp masking sharpens an image by increasing edge contrast using the difference between the original image and a blurred copy. Its principal controls are commonly radius, amount, and threshold.

How Unsharp Masking works

Unsharp masking derives a detail signal by blurring an image and subtracting that result from the original, then adds a scaled version of the difference back. Radius selects the spatial scale treated as an edge, amount controls the contrast increase, and threshold can protect small variations. Because the filter alters local contrast rather than recovering detail, its settings must suit resolution and noise. It commonly follows resizing near the end of an image derivative pipeline.

Key facts

  1. A small radius emphasizes fine edges, whereas a larger radius affects broader transitions and is more likely to create visible bright and dark halos around high-contrast boundaries.
  2. Thresholding can prevent low-amplitude differences from being sharpened, reducing noise amplification in flat areas, but an excessive threshold also leaves legitimate subtle texture untouched.
  3. Sharpening before a major downscale often enhances detail that resampling later removes; applying it after final sizing lets the radius correspond to the actual output pixel grid.

When Unsharp Masking matters

Apply unsharp masking after resizing when resampling has reduced apparent edge clarity. Excessive radius or amount can create halos, amplify noise, and make compression artifacts more visible.

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