Image Tools
Image Histogram Viewer - Analyze RGB & Luminance Distribution
Upload any image to instantly view its RGB and luminance histogram. Analyze tonal distribution, exposure, and color balance - all in-browser, no upload.
Click or drag & drop an image
PNG, JPEG, WebP, GIF, etc.
Ideal histogram shapes for different scenes
There is no single "perfect" histogram shape - it depends on the subject:
- Portraits: slight right-weighting ("expose to the right") maximizes signal-to-noise in the darker shadow areas without clipping highlights.
- Landscapes: watch for clipping at both edges. A histogram touching the left wall means lost shadow detail; touching the right wall means blown highlights.
- High-key images (white backgrounds, bright subjects): intentionally right-weighted histograms are correct, not overexposed.
- Low-key / dark scenes: intentionally left-weighted histograms are correct for night scenes and dark portraiture.
Histogram workflow: expose in-camera, adjust in post
The recommended workflow for photographers:
- Check the histogram on your camera's LCD after each shot, not just the image preview.
- Expose to avoid clipping - especially protect highlights, as blown highlights are unrecoverable in JPEG. Raw files have more latitude.
- In post-processing (Lightroom, Capture One), use the histogram to guide exposure, highlights, and shadows adjustments.
Raw files capture 12–14 stops of dynamic range vs. 8–10 stops for JPEG, giving significantly more latitude to recover clipped shadows and highlights in post.
What is an image histogram?
An image histogram is a graph showing the distribution of pixel intensities in an image. The horizontal axis represents brightness values from 0 (black) to 255 (white), and the vertical axis shows how many pixels have each brightness value. Histograms are a fundamental tool in photography and image editing for assessing exposure, contrast, and color balance.
How to read a histogram
| Pattern | What it means |
|---|---|
| Spike at left (0) | Clipped shadows: detail lost in dark areas |
| Spike at right (255) | Blown highlights: detail lost in bright areas |
| Bell curve in center | Well-exposed image with full tonal range |
| Bimodal peaks | High-contrast image with both bright and dark areas |
| Skewed left | Underexposed / dark image |
| Skewed right | Overexposed / bright image |
Channels explained
- Red, Green, Blue: per-channel intensity distribution.
- Luminance: overall brightness using BT.709 coefficients (
0.2126R + 0.7152G + 0.0722B), matching how human eyes perceive brightness.
Privacy note
Your image never leaves your device. All histogram computation happens locally in the browser
using the Canvas getImageData API.