Furthermore, while it CAN be used as a standalone program, DeNoise gives the user no control over the format in which to save. I had to always keep its “Remove Noise” setting at High to get comparable results, as leaving it at Medium resulted in luminance noise still being high, though the program handled color noise well in that setting. Using this model with its preferences set to Auto still proved insufficient, though. I therefore chose “Clear” instead of “Standard”. It has several other AI models that each come with their own default settings. One exception from the above warrants a separate discussion: In its standard setting, Topaz DeNoise AI sometimes achieves little noise improvement and uneven noise removal, certainly nowhere near what the program is capable of. The images shown below represent 100% crops from these exported images, each of them 1,000×1,000 pixels large. In order to avoid artifacts, each image was exported with a quality setting of 100, which meant large files.
In case of Lightroom and because of the way this program works, this meant an interim conversion to the DNG file format.
Each program was also blocked from doing anything else with the image, meaning that I loaded the RAW file, selected the noise reduction at the program’s default settings, disabled all other editing functions, and exported the image as a JPEG. It is also omitted from this test.Īll test shots were processed at each program’s default settings for the respective NR engine. Furthermore, Topaz recently released Photo AI, which combines their DeNoise, Sharpen and Gigapixel AI apps. (Truth be told, DxO still also offers the old PRIME engine, but that one performs rather poorly when compared to the others.) DxO’s PureRaw uses these same NR engines and is therefore not part of this comparison. Note: DxO has two different NR engines, DeepPRIME and DeepPRIME XD.
BROOM GRIPPER SOFTWARE
The noise reduction software contestants in this test are: Together with the high overall noise level caused by that camera’s much smaller sensor and the fact that the shot is underexposed, this presents a particular challenge for any NR engine.
BROOM GRIPPER ISO
The OM-1 test shot, taken at an ISO of 16,000, shows the most color noise. The Nikon D850’s noise pattern is less uniform than the Canon’s and the shot looks as noisy as, maybe even more so than, the Canon one, while the Nikon’s ISO setting was quite a bit lower at 10,000. This particular shot is slightly unsharp, though not by much. The image taken with the Canon R5 has the most acceptable looking noise, in spite of having been shot with the highest ISO setting, at 25,600, which is testimony to that body’s excellent low-noise performance. The images shown here were converted to JPEGs in DxO PhotoLab without any edits, then cropped to 1,000×1,000px. Here are the three original test images used for the comparison. (I also owned Nikon’s Z7 and Z7ii mirrorless cameras at some point but never took high-ISO shots with either, since their AF performance was lacking in low light.)įor comparison purposes, I also included CaptureOne’s noise reduction in the report. In Nikon’s case, I am using a test image that was shot with a DSLR, whereas the R5 and OM-1 are mirrorless bodies. Since I own all of these software packages, and as I have or used to have cameras from different brands, I thought it would be worthwhile to test each software’s NR performance with high-ISO images taken with each of three different bodies, a Canon R5, a Nikon D850, and an Olympus/OMDS OM-1. Previously a weak player that could not hold a candle to the other three, Adobe Lightroom’s latest revision adds an AI denoising engine (“Enhanced NR”) that according to the company delivers excellent results. The fourth contender is the “New kid on the block” when it comes to strong denoising performance. At the time of this writing, three of them have a reputation of being the best of the best when it comes to noise reduction (NR), namely Topaz DeNoise AI, DxO PhotoLab (with its DeepPRIME and DeepPRIME XD algorithms), and ON1 PhotoRaw (with its NoNoise AI algorithm). This report summarizes a comparative test of the denoising performance of four different image processing software programs.
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