Source: https://restorebunny.com/guides/dust-versus-stars-in-night-photo-scans/

# Dust or Stars? Review Bright Dots in Night Photo Scans

Use source context and alternate captures before deleting small bright points from a night scene.

Restoration techniques2 min readUpdated 16 October 2026

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Quick answer

## The short version

A bright dot in an old night photograph may be dust, a star, a light or a damaged pixel in the capture. Do not remove every isolated point under a universal cleanup rule. Compare the original and any alternate exposure or scan, and preserve unresolved details when evidence is insufficient.

## Define the job before editing

A bright dot in an old night photograph may be dust, a star, a light or a damaged pixel in the capture. Do not remove every isolated point under a universal cleanup rule. Compare the original and any alternate exposure or scan, and preserve unresolved details when evidence is insufficient.

## Use location and repetition as clues

Check whether dots cross borders, repeat at the same capture coordinates or follow features in the scene. Inspect several regions rather than a single enlarged crop. Avoid allowing an automated cleanup setting to erase a constellation, distant windows or other small but meaningful subject detail.

## Make the decision from evidence

Document what is known and what was deliberately left unchanged. If an editor removes points for a decorative display copy, label that as an interpretive choice. The source image remains the evidence for what was visible before cleanup.

## A worked planning example

Example: A white point appears in the same scanner coordinate across three unrelated prints. That is different evidence from several points that remain in the night sky when the print is rotated and captured again.

## A practical checklist

1. Inspect the source and borders.
2. Compare independent captures when available.
3. Avoid indiscriminate dot removal.
4. Record unresolved points and interpretive edits.

## Keep a traceable result

Keep the source file, the working copy and the delivery copy as separate items. Record the input and the changes you actually made so another person can understand the result later. These workflow examples are planning examples, not documented customer outcomes or proof of a successful restoration.

## FAQs

Can AI reliably classify every tiny bright dot?

No. Small ambiguous features may be reconstructed or removed incorrectly. Use source evidence rather than a blanket cleanup assumption.

Should I replace my original with the edited copy?

Keep the source unchanged and save a separate working or sharing copy. An export, edit or AI interpretation can omit information that remains useful in the source.

## Sources

Preservation and technical guidance reviewed for this article.

- MDN Web Docs: [Pixel manipulation with Canvas](<https://developer.mozilla.org/en-US/docs/Web/API/Canvas_API/Tutorial/Pixel_manipulation_with_canvas>)

## Related

- [Open the related free tool](<https://restorebunny.com/tools/annotate-image/>)
- [Diagnose Scanner Banding Before Retouching a Photo](<https://restorebunny.com/guides/diagnose-scanner-banding-before-restoration/>)
- [Moiré Patterns in Scans of Printed Photos](<https://restorebunny.com/guides/moire-patterns-in-scans-of-printed-photos/>)
- [Browse photo guides](<https://restorebunny.com/guides/>)
- [Free image tools](<https://restorebunny.com/tools/>)

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