Navigate to the Develop tab and scroll down to the Detail options. And, like Photoshop, it has some stock noise reduction tools available. Our other go-to editing software is Lightroom Classic. There are additional options, like being able to target noise by color channel.Īnd there are additional settings that will help try to recover any details that might have been lost with the noise reduction effect, but we found that, with this particular image, they just tended to reintroduce grain back into the image. Notice that, while some noise was removed, there’s still quite a bit remaining in the image. Within the Reduce Noise dialog, set the Strength of the effect to 10.
This will help us see the results better, exaggerated as they may be. Throughout these tests we’re going to be dialing up the noise reduction settings of each program to max. Hover over the Noise option and select Reduce Noise.
You can find the noise options under the Filter menu. This will convert all Filters to Smart Filters, which allows them to be disabled, removed, or adjusted at any time. Since the noise reduction option in Photoshop comes as a filter, it’s a good idea to first right-click on the image layer and select Convert to Smart Object. Photoshop is our home base when it comes to photo editing, so there’s no better place to start. We’ll be looking for the program that can remove the most noise while sacrificing as little of the original definition and detail in the photo as possible. Let’s take a look at some of the most popular programs out there, from our usual suspects like Photoshop and Lightroom Classic, to newer tools like Luminar AI, DxO PhotoLab, Topaz DeNoise, and Vance AI. With more devices out there capturing noisier photos, it’s no surprise then that noise reduction editing technology is on the rise. It’s even more common with portable digital cameras, like those found in mobile phones, since those devices have a limited dynamic range and a limited range of options for shutter speed and aperture settings. Noise often appears in images that are underexposed or were captured at a high ISO to compensate for environmental lighting conditions.
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