How to Remove Sensor Dust from RAW Photos in DxO PhotoLab 10
Sensor dust is one of those problems that becomes obvious only when you have finished a shoot. A mark may disappear in a portrait with a soft background, then show up repeatedly in a bright sky or a product photograph made at a smaller aperture.
DxO PhotoLab 10 adds automatic dust-spot detection and removal at the RAW stage. For me, the useful question is not whether a computer can find a mark. It is whether the result can be checked quickly and applied consistently without accidentally removing something that belongs in the photograph.
What the new dust tool is designed to do
DxO describes the feature as AI-powered detection and removal of sensor dust and small imperfections within the RAW workflow. That means it is intended to address a recurring technical problem before you reach the creative finishing stage. It is distinct from changing the look of a photograph or using a general-purpose content-generation tool.
Automatic detection is a starting point, not a guarantee that every mark will be identified correctly. Dust can overlap texture, fine branches, patterned clothing or other image detail. Review matters most where the correction touches a subject edge.
Start by checking the source files
Choose several representative RAW images from the same camera session. Include one with a plain bright area, one with fine detail and one with the kind of subject you normally deliver. Inspect at a useful magnification so you know what genuine dust looks like in the set.
If the marks are fixed in the same sensor coordinates across multiple images, that is a strong clue that they are sensor contamination rather than something in the scene. Remember that cropping, stabilisation and image orientation can change where the marks appear on screen.
Build a repeatable cleanup pass
Open the images in PhotoLab 10 and locate its automatic Dust Removal controls. Apply the feature to a test file, then inspect both the correction and the surrounding detail at 100%. If the result is clean, extend the approach to the remaining photographs as supported by your version and workflow.
Before exporting the whole set, check a small selection again. Large smooth areas are useful for spotting missed marks; detailed areas are useful for spotting false positives. For a client job I would rather spend an extra minute checking than deliver dozens of photographs with the same bad correction.
Why batch work still needs judgement
Photographers often want a one-click answer because dust tends to repeat across an entire shoot. That repetition makes batch processing attractive, but it also means a bad assumption can repeat. The correct response is to build a controlled workflow with representative checks rather than blindly trust an automatic pass.
If an image contains complex detail where a dust mark crosses a meaningful feature, finish that particular spot manually. Automation should reduce the repetitive workload; it should not remove your ability to make a more careful correction where required.
What the software cannot fix
Dust removal does not replace keeping the camera sensor reasonably clean. It also cannot guarantee a perfect reconstruction of information hidden by a large contaminant. For persistent spots, a proper sensor-cleaning procedure remains part of camera maintenance.
Equally, not every small dark mark is dust. A distant bird, a freckle, texture in a wall or a deliberate part of the scene can look similar at thumbnail size. That is why the photographer still needs to decide what belongs.
Where this fits into a RAW edit
I would place dust cleanup alongside other technical preparation: optical corrections, noise reduction, exposure and white balance. Once those foundations are stable, move on to local colour, contrast and any creative finishing. There is little value in perfecting a grade while a repeated sensor mark is still distracting the eye.
The best test is a real batch from your own camera, not a single promotional before-and-after. Compare how much time you save after checking the corrections. That tells you whether the feature is genuinely useful for the type of work you produce.
Frequently asked questions
Is automatic dust removal new in PhotoLab 10?
Yes. DxO lists AI-powered sensor dust detection and removal among PhotoLab 10 features.
Does it replace sensor cleaning?
No. It addresses image corrections, not the physical cause of dust on the sensor.
Should I inspect the output?
Yes. Review both missed spots and unintended corrections, particularly in detailed areas.