Image & Logo Generation Prompts
Photo Restoration and Colorization Brief Builder
Create a conservative image-restoration brief that repairs damage, preserves identity and period detail, and separates evidence from colorization guesses.
FreeChatGPTMidjourney
Best for
Families, archivists, historians, and creators restoring damaged photographs without erasing authentic features or presenting invented colors as fact.
Suitable LLM groups
FrontierReasoning
Prompt
You are a photographic restoration specialist who prioritizes historical fidelity, identity preservation, and reversible editing decisions.
Inputs:
1. Photograph subject, date, location, and provenance: {{photo_context}}
2. Visible damage and image-quality problems: {{damage}}
3. Known identity, clothing, object, and setting details: {{known_details}}
4. Restoration and optional colorization goals: {{goals}}
5. Historical references and changes that are not allowed: {{constraints}}
Do the following:
1. Inventory the visible defects by region, separating dust, scratches, folds, stains, fading, blur, missing areas, compression, and scanning artifacts from authentic photographic texture.
2. Define preservation priorities for facial geometry, expression, body shape, clothing construction, objects, architecture, film grain, lighting, and crop; explicitly forbid beautification or modernization unless requested.
3. Create an ordered restoration plan that starts with global stabilization and proceeds to local repairs, stating where reconstruction is evidence-based, uncertain, or inappropriate.
4. If colorization is requested, build a color-evidence table using supplied references and period-plausible ranges, clearly marking verified, inferred, and unknown colors.
5. Write a complete image-editing prompt plus negative constraints, a quality-control checklist, and two outputs: a faithful restored monochrome master and, if requested, a separately labeled colorized interpretation. Require human review for faces and large missing regions.How to use
- Scan at high resolution and preserve the untouched original.
- Describe known historical details and their evidence.
- Separate restoration from optional colorization.
- Review faces and reconstructed regions at full resolution.
Example input
Context: Studio portrait of my grandparents in Izmir, Turkey, around 1954; scanned from a 9 x 14 cm print at 1200 dpi. Damage: diagonal crease through the man’s jacket and background, silvering at edges, dust, low contrast, and a 12 mm missing corner that contains only backdrop. Known details: his suit was charcoal; her dress was deep teal according to a surviving fabric piece; both had dark brown eyes. Goals: faithful repair, monochrome master, and a separate restrained colorization. Constraints: do not smooth skin, reshape faces, whiten teeth, change hairstyles, invent jewelry, or replace the studio backdrop.
Example output
The plan preserves facial features, pores, hair edges, original crop, and film grain while repairing dust, silvering, and the crease in small passes. The missing corner may be reconstructed from the plain adjacent backdrop, but no missing facial or clothing detail is invented. The color table marks charcoal suit and teal dress as sourced, brown eyes as family-confirmed, and skin, backdrop, and tie colors as inferred ranges. Separate prompts produce an archival monochrome master and a clearly labeled colorized interpretation.
Customization tips
- — Mark each color as verified, inferred, or unknown.
- — Specify authentic grain and sharpness to preserve.
- — List prohibited beautification changes explicitly.
- — Keep a monochrome master even when colorizing.
Tags
#photo-restoration#historical-colorization#image-editing#archive-preservation#visual-fidelity
FAQ
What is this prompt for?
It creates a conservative restoration and colorization brief that repairs damage while preserving identity, period detail, and uncertainty.
How should I customize it?
Provide a high-quality scan, approximate date and place, damage description, known colors or objects, reference evidence, and prohibited changes.
Are there any limitations?
Large missing regions and unknown colors cannot be recovered as facts; generated reconstruction and colorization remain interpretations requiring review.
How is it different from a basic prompt?
It separates defects from authentic texture, labels reconstruction confidence, preserves a monochrome master, and distinguishes verified colors from plausible guesses.
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