Image Histogram Viewer
Drop an image — JPG, PNG, WebP, GIF, anything your browser decodes — and read its tonal distribution. Per-channel RGB and luminance histograms with min, max, mean, median, standard deviation, plus clipping warnings for blown highlights and crushed shadows. Everything runs locally; your image never gets uploaded.
Image
What the bars mean
A histogram counts how many pixels fall into each brightness bucket from 0 (black) to 255 (white). Tall bars on the right side mean lots of bright pixels; tall bars on the left mean deep shadows. A spike crammed against either edge is clipping — pixels lost detail because they exceeded the captured range. A balanced photo usually has data spanning the whole 0–255 range without spikes at either end.
The luminance channel uses the BT.709 weighting (Y = 0.2126·R + 0.7152·G + 0.0722·B) — the same formula your TV and most image editors apply to compute perceived brightness. Mean < 64 hints at an underexposed shot; mean > 192 hints at overexposure. The standard deviation is a rough proxy for contrast — a flat, foggy image has low σ; a high-contrast scene with deep shadows and bright highlights has high σ.