Free web tool

Image histogram analyzer

Analyze RGB and luminance histograms plus basic pixel statistics in the browser.

Input & settings

How to use

Plot the distribution of R, G, B, and luminance values from 0 to 255. It helps you see whether an image is concentrated in shadows or highlights and whether one color channel dominates, instead of relying on appearance alone.

  1. Choose an image.
  2. Choose the sampling step. For large images, 2 / 4 / 8 px reduces work. For transparent images, decide whether fully transparent pixels should be excluded.
  3. Run the analysis and review the overlaid histograms, channel averages, luminance average, and sampled-pixel count.

A histogram answers “how many pixels have each value?”

The horizontal axis runs from 0 to 255 and the height shows how many sampled pixels land at each value. The tool overlays R, G, B, and luminance, where luminance uses perceptual weighting rather than a simple RGB average.

A distribution pushed left contains more dark values; one pushed right contains more bright values.

v1.49 applies the sampling step in both directions

Previously, a 4 px step advanced through the flattened pixel array rather than sampling a true 4 px grid. v1.49 fixes this: 4 px now means every fourth pixel in x and every fourth row in y.

Use 1 px when you want every pixel; larger steps make analysis much faster on large images.

Hidden RGB under transparent pixels can skew the numbers

Fully transparent pixels can still store RGB values even though those colors are invisible. Including them can make averages and histograms disagree with what the image looks like.

v1.49 defaults to excluding fully transparent pixels. Turn that option off only when you intentionally want to inspect the hidden RGB data.

An average does not describe contrast by itself

Two images can have the same average luminance but very different distributions: one clustered in midtones, another split between deep shadows and bright highlights.

Treat averages as a quick summary and read the histogram shape too. To edit the image afterward, use Brightness / contrast / saturation.