Exposure Analyzer

What it does

Builds a brightness histogram from the photo (256 levels, black to white) and reads it for common exposure problems: how much of the image is near-pure-black (shadow clipping), how much is near-pure-white (highlight clipping), and where the average brightness sits.

What you'll need

• A photo (JPEG, PNG, WebP, etc.) from your device.

Steps

1. Tap "Upload a photo" and choose an image.
2. The histogram and clipping percentages appear automatically.
3. Upload a different exposure/edit of the same shot to compare.

Reading the result

The bar chart is the histogram — the horizontal axis runs black (left) to white (right), and bar height shows how many pixels sit at that brightness. A tall spike hard against the left or right edge usually means clipping (detail permanently lost in that area, not recoverable by editing). Clipping above 5% at either end is flagged in the verdict: "Highlights clipping" or "Shadows blocking up", or "Overexposed" / "Underexposed" when the mean brightness is also high (over 185) or low (under 70). Clipping above 5% at both ends reads "High contrast".

Tips

• Some clipping is intentional and fine — a silhouette against a bright sky, or a genuinely black background, will show heavy clipping without being a mistake.
• "High contrast" (clipping at both ends) is common and often desirable in high-contrast scenes like backlit subjects — it's a description, not necessarily a problem to fix.

What is a brightness histogram?

A histogram is a bar chart of every pixel in a photo sorted by brightness, from pure black on the left to pure white on the right, with bar height showing how many pixels sit at that level. This tool builds one from your photo across 256 brightness levels and reads it for two specific problems: how much of the image is clipped to near-pure-black (shadow clipping) and how much is clipped to near-pure-white (highlight clipping).

Why photographers use it

A camera's rear LCD or a phone screen can lie about exposure, especially outdoors in bright sunlight where the screen itself is hard to read accurately. Checking the actual histogram — in-camera while shooting, or here afterward — catches blown highlights or crushed shadows a screen glance would miss. That's detail that's genuinely unrecoverable once clipped, unlike a shot that merely looks dark or bright on screen but still holds real information in the file.

Common mistakes

• Treating all clipping as a mistake to fix. a silhouette against a bright sky, a genuinely black background, or a light source in frame will show heavy, correct clipping. The verdict describes what's in the histogram — it isn't automatically a flag that something went wrong.
• Judging exposure from mean brightness alone. a photo can show a "correct" average brightness while still clipping significantly at both ends in a high-contrast scene. Check the clipping percentages separately from the mean brightness figure.
• Expecting this tool to recover clipped detail. it only flags clipping — it doesn't fix exposure or restore lost highlight or shadow data. Once detail is genuinely clipped in the file you upload, no analysis tool, this one included, can bring it back.
• Reading "high contrast" as the same thing as "poorly exposed". clipping at both ends is common and often intentional in backlit or dramatic-lighting scenes. It's a description of the light in the scene, not necessarily a reason to reshoot.
• Analysing an edited or compressed copy instead of the original. heavy compression and prior edits change the actual pixel values the histogram reads. A screenshot or re-compressed copy can show different clipping than the original file actually has.

Example settings

FAQ

What actually counts as "clipping"?

Pixels at or next to pure black (levels 0-4) or pure white (levels 250-255) on the 256-level scale — detail that's effectively lost, with no information left in those pixels for editing to recover. More than 5% of the image at either end is flagged in the verdict; the Histogram tool uses the same levels and the same 5%.

Why does the verdict say "High contrast" instead of over- or underexposed?

Because clipping is present at both ends at once, meaning neither a single "brighten" nor "darken" edit would fix both. It describes a scene whose dynamic range exceeded what the camera captured — not a single-direction exposure error.

Is some clipping always a problem?

No. Genuinely black backgrounds, silhouettes, and light sources in frame are supposed to clip. Read the percentage alongside what's actually in the photo, not as a number in isolation.

Is my photo uploaded anywhere?

No — this runs entirely in your browser. Nothing is sent to a server for this tool.

Can this fix my exposure or suggest specific edits?

No — it flags clipping and gives a plain verdict. For actual edit suggestions, try the AI Editing Suggestions tool, a separate AI-vision tool built for that.