Do Z
Includes Z/depth data in the gain operation when applicable.
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Color & Image ProcessingBeginner
AutoGain
Automatic range normalization
Automatically remaps image values from a detected low/high range to a normalized output range, with optional Z processing.
AutoGain
DaVinci Resolve · Fusion
AutoGain is a utility correction that quickly stretches or normalizes tonal data. It is useful for diagnostic passes, depth data and images whose useful values occupy only a narrow range.
Overview
What AutoGain does
AutoGain is a utility correction that quickly stretches or normalizes tonal data. It is useful for diagnostic passes, depth data and images whose useful values occupy only a narrow range.
Mental model
Find the useful low and high limits, then stretch that interval so it fills the available range.
Common uses
Normalize a flat technical pass
Stretch matte contrast
Make depth data easier to inspect
Quickly expand a narrow value range
Flow anatomy
Inputs & outputs
The port structure shows how this node fits into a Fusion graph.
Input
Source image for the operation.
Effect Mask
Optional mask that limits the operation to selected areas.
AutoGain
Fusion node
Output
The processed result from this node.
Inspector
Important parameters
Start with these controls before reaching for more complicated workarounds.
Low
Sets or represents the lower normalization bound.
High
Sets or represents the upper normalization bound.
Settings / Blend
Sets how strongly the processed result is mixed into the image.
Settings / Process R G B A
Selects which RGBA channels are processed by the node.
Settings / Effect Mask
Limits the effect to the connected mask.
Practical setup
A reliable workflow
- 1
Inspect the incoming value range.
- 2
Choose the channels that should be normalized.
- 3
Set Low and High appropriately.
- 4
Enable Z only when depth data is intentional.
- 5
Check that clipping is not destroying meaningful values.
Typical node chain
Input→
AutoGain→
Output
Examples
Where this node fits in real work
Matte normalization
Expand a weak grayscale matte before downstream use.
MatteAutoGainBitmap
Depth visualization
Normalize Z data for easier inspection.
Depth PassAutoGainViewer
Troubleshooting
Common mistakes
Normalizing RGB when only a matte was intended
Clipping useful highlights or shadows
Treating automatic normalization as final creative grading
Production notes
Practical tips
Use AutoGain as a technical preparation step, then grade deliberately.
Check channel selections before applying it to multi-pass imagery.
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