My Tools Garage

Image Histogram Viewer

See the tonal and colour distribution of any photo.

in-browser

How to use

  1. 1 Drop an image onto the box, or click to choose a file.
  2. 2 Pick a channel: Luma, Red, Green or Blue.
  3. 3 Read the distribution — left is dark, right is bright, height is pixel count.
  4. 4 Optionally download the histogram chart as a PNG.

About Image Histogram Viewer

The Image Histogram Viewer reads any photo and plots how its tones and colours are distributed, the same chart professional editors lean on to judge exposure.

Drop in a JPEG, PNG, WebP or GIF and it is decoded and analysed entirely inside your browser using the Canvas API, then drawn as a clean bar chart you can flip between channels.

A histogram is the most honest way to read an image.

The horizontal axis runs from pure black on the left to pure white on the right, and the height of each bar shows how many pixels share that intensity.

A spike jammed against the right edge means blown-out highlights; one piled on the left means crushed shadows; a lopsided red or blue curve betrays a colour cast you might not notice by eye.

Switching between the Luma view and the individual Red, Green and Blue channels lets you diagnose all of this in seconds.

For speed, large images are sampled down to a representative size before counting, and fully transparent pixels are ignored so they do not flatten the chart.

Everything happens on your own device — nothing is uploaded, stored or logged — so it is safe for private or client images and keeps working offline.

You can download the rendered histogram as a PNG to drop into notes, reports or a before-and-after comparison.

FAQ

Is my image uploaded anywhere?

No. The picture is decoded and analysed with the Canvas API inside your browser, so it never leaves your device.

What does the luma channel show?

Luma is perceptual brightness using the Rec. 601 weighting, giving a single curve that reflects how light or dark the image looks overall.

Why does a huge image still analyse quickly?

Very large images are scaled down to a representative size before counting, which keeps the chart fast while preserving the overall shape.