DeNoise AI 3.3 used for image on the left. See the comparison images below, in both images, the deNoise treated image is on the left (click on images to enlarge): Mountain detail. (And I thought I was thrilled with DeNoise AI before this new version.) You can then save the image as DNG if you wish to take the greatest advantage of the Lightroom Develop module or Camera Raw in Photoshop. All using the raw sensor data from the camera. Not only does it do a great job on the noise, but it does an amazing job of clarifying and sharpening images at the same time. The new RAW model works from the original raw sensor data. As the name implies, it works on RAW files that can then be saved as tiff, psd, jpg, png, or dng. Topaz has added a new noise reduction model to DeNoise AI called RAW. That workflow just got a kick in the pants with the latest version of Topaz DeNoise AI (3.3). The reasons I do this are that DNGs don’t need xmp sidecar files and they have a smaller file size than the raw files from the camera, in my case, Nikon NEF files. The last thing I do before I send the images off to their archiving home is to convert them to DNG (deleting the original raw files). Mostly I just want to get the images imported, culled, and add metadata and ratings. But I usually don’t do a lot of image editing at this point. Some will go to Photoshop for anything that can’t be done in Lightroom. I usually will do some image editing at this point, mostly in Lightroom but some will go to DeNoise AI and saved as tiff files. I’ll delete all the images marked with an X and then make sure all remaining images have keywords, captions, and location information. Subsequent passes may increase star ratings and usually add a few more images to the delete pile. And I add bulk and then specific metadata.
Ai denoise series#
I add color labels to images that are to become part of a panorama, exposure or focus blending series of images, teaching images, etc. Up until now my workflow for new images brought into Lightroom has been to do a few passes of culling, which involves marking some images with either a star for early favorites, a reject tag (X) for definite deletes, and no markings for decent but not outstanding images.
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