# How to make AI images look real

Source: https://passreal.com/how-to/make-ai-images-look-real

An AI image looks fake when it is too perfect: plastic skin, flawless light, odd hands and text, an evenly blurred background and no grain. Fix the eye first with a prompt that asks for natural light, a phone lens and small flaws, then retouch the weak spots. Fix the file last: add sensor grain and lens fringing, and save a camera JPEG with real phone EXIF. PassReal handles that last part in one upload, and the first 3 images are free.

## Two ways an AI image gets caught

People ask how to make AI images look real as if there were one problem. There
are two, and they need different fixes.

The first is what the eye sees. A viewer has a feeling that something is off
before they can say why. The second is what the file shows. A system does not
have feelings. It reads the records inside the file and the statistics of the
pixels. An image can pass one test and fail the other, so it pays to handle both
in order.

## What gives it away to the eye

- Skin without texture. No pores, no fine lines, an even shine. See
  [how to fix plastic skin in AI images](/how-to/fix-plastic-skin).
- Light that is too good. Soft, even, flattering light on every subject, with
  no harsh shadow and no blown highlight.
- Hands and fine structure. Extra or fused fingers, rings that melt into skin,
  glasses with mismatched arms.
- Text. Signs, labels and shirt prints with letters that almost work.
- Background blur. The same soft blur everywhere, instead of focus that falls
  off with distance.
- Symmetry and tidiness. Faces, rooms and crowds that are too orderly.
- No grain. Even in good light, a phone photo has fine noise, and it is easy to
  see when it is missing.

## Prompting for realism

The cheapest fix is at generation. A few habits change the result a lot.

Describe a camera that real people use: a phone main lens, a casual snapshot,
window light on a cloudy day. Say where the light comes from, since "natural
light" alone is vague. Ask for ordinary imperfections such as a creased shirt,
mixed colour temperature or something slightly out of place on a shelf. Drop
the quality words. Terms like masterpiece and ultra detailed push a model toward
the polished look you are trying to avoid.

Ask for fewer subjects as well. Every extra hand, face or sign is another place
to go wrong.

## Retouching what is left

Zoom to full size and work in this order: hands, text, edges, skin. Inpaint
small regions rather than regenerating the whole frame, so you keep what
already works. Then adjust the picture as you would a phone shot: slightly
lower contrast, softer highlights, a colour balance that is a little off. Over
retouching brings the smooth look back.

## What gives it away to the file

Once the picture holds up to the eye, look at the file. Generators such as
Gemini, ChatGPT and Adobe Firefly write provenance records into the export: a
C2PA manifest, an IPTC field naming a trained model, XMP tool names. On one
Gemini export we counted 174 markers. The pixels are too clean, with none of the
brightness-dependent grain or lens colour fringe a sensor adds, and a generator
PNG has no camera EXIF.

You can clean this by hand. ExifTool removes the records, an editor adds grain,
and a JPEG export with matching EXIF finishes the job. PassReal does the same in
one upload: it strips every metadata family, simulates the sensor, smooths the
high frequencies and re-encodes as a camera JPEG, then shows SSIM and PSNR for
your image. Three images are free. The method in full is in
[how to add camera noise to an AI image](/how-to/add-camera-noise).

## Limits

This will not turn a weak picture into a strong one. It cannot remove SynthID,
which Google says survives edits, and it cannot remove a drawn logo or visible
text. If a public AI image detector flags an image you paid PassReal to process,
email us within 14 days and the payment is refunded, as set out in section 7 of
the Terms of Service.

## Questions

### Why do AI images look fake even when they are sharp?

Sharpness is not the problem. Models are trained on polished photographs, so they produce skin with no pores, light that falls too evenly, and backgrounds blurred by the same amount everywhere. Real photos have uneven focus, noise and clutter.

### Does adding grain make an AI photo look real?

It helps the surface feel less synthetic, but grain alone does not repair bad hands or plastic skin. Use it as the final step, after the image is already convincing to the eye.

### Can PassReal fix hands, text or skin?

No. It adds sensor-style grain and lens fringing, smooths the frequency spectrum, strips metadata and writes phone EXIF. Content problems have to be fixed at generation or by inpainting before you upload.

### Does making an image look real remove an AI label?

Not by itself. Labels such as Meta's AI info come from standard markers in the file and from what the user declares, so how real the picture looks does not change them. Cleaning the file is a separate step, and it does not remove SynthID or a visible watermark.

### Do I still have to disclose that an image is AI-generated?

Often yes. Platform rules and local law can require it, and a realistic result raises the stakes. Check the rules of the place where you publish.

Try it: https://passreal.com/app (three images free)