Explainer Noise Reduction RAW Workflow

What is DeepPRIME AI?

DeepPRIME AI is DxO’s approach to cleaning noise while keeping real detail. In simple terms: it helps your RAW photos look cleaner in low light and high ISO without turning textures into mush. This page explains it in plain English and when to use it.

What is DeepPRIME AI in DxO PureRAW 6

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DeepPRIME AI in one sentence

DeepPRIME AI is designed to reduce noise and rebuild fine detail in RAW files so your photo starts cleaner before you edit.


Why it matters (especially for high ISO)

Cleaner shadows

Noise often lives in the shadows. DeepPRIME is most useful when you lift exposure or shoot in low light.

Better texture

The goal is a natural look—less blotchiness, less colour speckling, and detail that still feels photographic.

Stronger starting file

Once the file is cleaner, Lightroom/Photoshop edits become easier and masking looks more refined.


When to use DeepPRIME AI

  • High ISO (indoor, night, concerts, street at dusk).
  • Underexposed RAW files where you need to lift shadows.
  • Small-sensor cameras where noise appears sooner.
  • Travel and street photography where you shoot fast and conditions change.

How to keep results natural

Do this

  • Use DeepPRIME as your default for “problem” files.
  • Judge results at 100% on real textures (hair, foliage, brick, fabric).
  • Keep sharpening for the end of your workflow.

Avoid this

  • Over-smoothing textures until everything looks waxy.
  • Sharpening noisy files early (it makes noise harsher).
  • Processing every image by default when only a few need it.
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FAQs

Is DeepPRIME AI only for high ISO?

It’s most noticeable at higher ISO and in low light, but it can also help with underexposed files where you need to lift shadows.

Will it remove all noise?

It can reduce noise dramatically, but the best results still look natural. A tiny amount of grain can be fine—over-smoothing usually looks worse.

How do I get the PureRAW discount?

Click through and use code SIMONSONGHURST at checkout.


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