Image Analysis · In-browser

Image Histogram Viewer — RGB & Luminance Distribution

Upload an image and instantly see its histogram: luminance plus R / G / B channel curves, with mean, median, standard deviation and shadow/highlight clipping percentages to judge exposure and color balance. Computed locally in your browser — no upload. Works on desktop, tablet & mobile.

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Luminance / RGB histograms & exposure hints · Computed locally, no upload
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Works on desktop, tablet & mobileNo upload — stays on your deviceNo watermarkLocal processing
Quick answer

A histogram is the health report of a photo’s exposure: the horizontal axis runs from shadows to highlights (0-255), the vertical axis counts pixels at each level. A distribution squeezed left means a dark image (underexposure tendency); squeezed right means bright (overexposure); a "cliff" at either end means shadow or highlight detail is already lost. This tool counts every pixel locally in your browser: the luminance histogram uses the perceptual 0.3R+0.59G+0.11B weighting, and separate R / G / B and overlay views reveal color casts. You also get mean, median, standard deviation (contrast) and clipping percentages at both ends, plus a plain-language interpretation. Everything runs locally — no upload.

When

When you need this

Photo review

Check exposure balance and end clipping after a shoot.

Before editing

Read the distribution before lifting shadows or taming highlights.

Color cast check

Strongly shifted RGB channels usually mean white balance is off.

Trade-off

Reading a histogram

It tells you
  • Whether the distribution covers the range — headroom at both ends is usually healthy
  • Clipping percentages — whether shadow/highlight detail is already gone
  • Whether RGB channels align — big offsets usually mean a color cast
Do not misread
  • There is no "correct" shape: snow scenes lean right, night scenes lean left — both are normal
  • It is a global statistic: a small blown-out area may barely show in the curve
  • Large images are downsampled proportionally; the distribution shape is unaffected
FAQ

Histogram FAQ

There is no single answer. Generally a wide distribution without cliffs at either end means balanced exposure and intact detail — but snow or high-key portraits naturally lean right, night scenes lean left, and both are fine. The histogram confirms your intent; it does not force every photo into one shape.

Clipping means pixels piled up at the extremes: a spike at 255 means blown "pure white" highlights, a spike at 0 means crushed "pure black" shadows — detail there cannot be recovered in editing. The tool reports the pixel share in the outermost 5 levels at each end; above roughly 2% deserves attention.

The luminance histogram blends the three channels with perceptual weights (green weighted highest) into one curve for judging overall brightness. The RGB view draws each channel separately — when the three curves are clearly offset, you likely have a color cast or white balance issue. Use luminance for exposure, RGB for color.

No. Pixel counting happens locally in your browser; large images are downsampled proportionally first (which does not change the distribution shape). Nothing is sent over the network or stored.