Fix weak, flat, or over-processed LUT outputs
Unexpected output is usually from prompt direction mismatch. Iterative refinement solves most issues without redoing from scratch.
Weak output symptoms
Flat looks usually mean insufficient contrast and/or low color separation in prompt constraints.
- Add explicit contrast and mid-tone guidance.
- Limit color cast while keeping blacks distinct.
- Request stronger highlights shaping.
Over-processed symptoms
Pushed saturation and harsh clipping happen when the prompt includes conflicting high-intensity adjectives with strong hue direction.
Corrective loop
- Use a restrained base output first (lower intensity words).
- Add one detail constraint in the second pass.
- Switch LUT size to 33³ if 17³ looks too coarse.
- Try alternate output format if your target app interprets colors differently.
Common Questions
Can I modify exported files manually?
Yes, but the safest path is usually prompt iteration first, then export a clean second pass.
Why does one format look different from another?
Different apps handle transforms and colorspaces differently. Export and compare the same prompt across supported formats.
Related guides
Writing effective prompts for better color grades
Good prompts are specific about visual intent, not only adjectives. This gives the generator stronger constraints.
Read guideCompare LUT and preset formats: .cube, .3dl, .look, .csp, .xmp, .lrtemplate
Each format was designed around a specific ecosystem. Picking the right file prevents import issues and avoids rework.
Read guide17³, 33³, 65³: when to use each LUT size
LUT size affects precision and processing load. Bigger is not always better; delivery and speed matter.
Read guideReady to generate?
Use these prompts as a starting point and generate in-app for your own imagery.