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Colourisation Memory Mismatch

We've colourised three archival photos this year and each time a client pushed back saying it felt made-up. Diagnose w…

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DBecome — “help me grow”We've colourised three archival photos this year and each time a client pushed back saying it…+
We've colourised three archival photos this year and each time a client pushed back saying it felt made-up. Diagnose where our colourisation process loses authenticity, and recommend one research habit and one restraint rule I should adopt so future colour references honour the original photo and still support the campaign's palette.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed.

The real tasks

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We keep tempting colourisation because it's pretty, then the client says it doesn't feel 'true' to memory.

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Art Director

Questions people actually ask

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Sometimes, the AI-generated pixels don't have enough detail or proper blending, causing print quality issues at large scales.

Always review your extension at 100% zoom to see if the AI blended pixels smoothly. Fix any rough edges or mismatched areas before printing.

Use the 'Match Evening Mood' or 'Replace Sky' tools to better blend the extension with the original image. Adding subtle color adjustments helps too.

Relying on the AI to perfectly blend without manually checking or refining the extension can lead to visible seams or mismatched areas in large prints.

A photo editor or retoucher doing large-scale prints will notice these failures during final proofing or print setup.

AI can create a convincing extension, but for large prints, manual touch-up or blending is often needed to ensure quality at final size.

Yes, it's related because both involve creating or blending new pixels, but generated extensions focus on AI inventing missing parts for printing.