Image Histogram
Analyze RGB and luminosity distributions with per-channel statistics and side-by-side comparison.
No watermarkFree & unlimited
All processing happens in your browser. No data is sent to any server.
About this tool
- 1
Upload an image
Select any photo or graphic to analyze its color distribution.
- 2
View the RGB histogram
See separate red, green, and blue channel distributions across the brightness range.
- 3
Analyze exposure
Check for clipping (spikes at the far left or right edges) indicating lost shadow or highlight detail.
- 4
Review statistics
See mean brightness, standard deviation, and channel balance data.
- A well-exposed photo has a histogram that spans the full range without clipping at either end.
- Heavy spikes on the left edge mean crushed blacks - shadow detail is lost.
- Heavy spikes on the right edge mean blown highlights - bright areas are pure white with no detail.
- Compare individual RGB channels to diagnose color casts - an unbalanced channel indicates a tint.
- Individual R, G, B channel histograms
- Luminosity histogram
- Clipping indicators
- Mean and standard deviation statistics
- Channel comparison overlay
- Evaluate photo exposure before and after editing adjustments.
- Diagnose color cast issues in product or studio photography.
- Verify print-ready images have proper tonal range without clipping.
- Learn photography exposure concepts with visual feedback.
There is no single ideal histogram - it depends on the scene. A well-exposed photo generally has data spread across the full range. A low-key (dark) scene will be left-heavy, and a high-key (bright) scene will be right-heavy, both intentionally.
Clipping means pixel values are pushed to pure black (0) or pure white (255). Clipped areas have no recoverable detail, which can make shadows look muddy or highlights look blown out.