![]() I tested PureRAW 2 by dropping raw Canon. It can work only on raw files as a stand-alone app, or as a plug-in from Adobe Lightroom. However, the exception is DxO’s PureRAW 2. So my workflow and test procedures reflect that. Many astrophotographers also choose to stack unedited original images with specialized stacking software, then apply further noise reduction and editing later in the workflow. But for my personal workflow I prefer to develop the raw files with Adobe Camera Raw, then open those into Photoshop for stacking and layering, applying any further noise reduction or sharpening as non-destructive smart filters. Most of these programs state that better results might be obtainable by using the stand-alone app on original raw files. METHODOLOGYĪs described below, while some of the programs can be used as stand-alone applications, I tested them all as plug-ins for Photoshop, applying each as a smart filter applied to a developed raw file brought into Photoshop as a Camera Raw smart object. The three test images in Adobe Camera Raw showing the Basic settings applied. For reasons explained below, I would not recommend DxO’s PureRAW 2.Other new programs, notably Topaz Photo AI and Luminar’s Noiseless AI, also need improvement before they are ready to be used for the rigours of astrophotography.While ON1’s new NoNoise AI 2023 performed fine, it proved slightly worse in some cases than its earlier 2022 version.For nightscapes and other images, Topaz DeNoise AI performed well, better than it did in earlier versions that left lots of patchy artifacts, something AI programs can be prone to.Of the group tested, the winner for use on just star-filled images is a specialized program for astrophotography, NoiseXTerminator from RC-Astro. ![]() The new AI-trained noise reduction programs can indeed eliminate noise better than older non-AI programs, while leaving fine details untouched or even sharpening them. But that does make the blog page slow to load initially. NOTE: All the images are full-resolution JPGs you can tap or click on to download for detailed inspection. Does one program stand out from the rest for astrophotography? To find out, I tested six of the new AI-based programs on real-world – or rather “real-sky” – astrophotos. How well can each program reduce noise without eliminating stars or wanted details, or introducing odd artifacts, making images worse. The new generation of programs use artificial intelligence (AI), aka machine learning, trained on thousands of images to better distinguish unwanted noise from desirable image content.Īt least that’s the promise – and for noisy but normal daytime images they do work very well.īut in astrophotography our main subjects – stars – can look a lot like specks of pixel-level noise. Over the last two years we have seen a spate of specialized programs introduced for removing digital noise from photos. ![]() In a detailed technical blog I compare six AI-based noise reduction programs for the demands of astrophotography.
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