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Posted on • Originally published at old-photo-restoration-saas.shop

Colorize Old Family Photos: A Workflow That Gets the Skin Tones Right

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title: "Colorize Old Family Photos: A Workflow That Gets the Skin Tones Right"
description: "Colorizing old family photos is different from random old photos: it is people you know. A complete workflow from scanning to AI colorization to manual touch-ups."
tags: [photography, aicolorization, familyhistory, tutorial]

canonical_url: https://old-photo-restoration-saas.shop/blog/colorize-old-family-photos

Colorizing old family photos is different from colorizing random old photos. Family photos are people you know: skin tones, clothing, the old objects in the background, none of it deserves a sloppy guess. Here is a complete workflow, from scanning to AI colorization to manual touch-ups.

Step one: scan quality sets the ceiling

AI colorization can only fill in colors that fit what it sees; everything it cannot see is a guess. Scan at 300dpi or higher. Fix creases and scratches before colorizing, restoration first. Export TIFF or high-quality PNG, never a social-app compressed copy. Most failed family colorization starts with a blurry source.

Step two: AI plus human touch-ups

Pure AI colorization is plausible but not always right: skin tones run cool, era-specific clothing colors get guessed wrong. The right pattern: let AI produce the first pass, check the three most visible things by hand (skin, sky or background, clothing), and fix skin tone with a warm shift.

For family photos, the manual steps are not optional. AI saves the 80% of grunt work; the remaining 20% is human judgment.

Step three: common portrait fixes

  • Face: skin looks gray or blue, warm up the color temperature 5-10% toward yellow-red
  • Lips and eyes: too pale or too vivid, use local selection adjustments, not a global filter
  • Clothing: color wrong for the era, reference period photos and shift the hue manually

Step four: saving

Keep two versions, the restored original and the colorized one; never overwrite the source. Export high-resolution for printing. Keep the before-after comparison, it is the most convincing proof of the work.

Try it on the free colorizer: https://old-photo-restoration-saas.shop/colorize

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