![]() ![]() iridient – Iridient X-Transformer 2.0.Speaking of DxO, recently they also added X-Trans support to DxO PureRAW 2.Īnd since we talk editing, I thought to make a mini-roundup with some of the editing related articles, including the ones of Thomas mentioned above in this article. If you are using DxO PhotoLab 5 already, feel free to let me (and us all) know in the comments what you think about it. A downside: in order to use Fujifilm’s film simulation, you have to purchase also the “ DXO Film Pack” as an extra. Thomas Fitzgerald, my go-to source for all things X-Trans files editing (links below) says that DxO is the best X-Trans converter for “ Pure Image Quality” in combination with DxO’s DeepPrime noise reduction technology. So much so, that, even though I am a hardcore CaptureOne user and lover, I think DxO PhotoLab 5 will be the one software I will check out in depth in 2022 as it seems to perform better than anything else. Please note that the number of activated systems is limited. Installing DPR on a new Mac also means that you’ll have to enter the activation code. ![]() ![]() ![]() And from all I could see so far, the results are absolutely fantastic. PureRaw’s standard installation is to drag the icon from the install window to the application folder. No, you can not test with an unsupported camera Morris But with any other supported camera - and it seems you did own supported cameras at the time. It seems that you have an issue with DxO PL more in general. DxO PureRAW 2 is a standalone raw conversion and noise reduction application for PC and Mac OS. It processed all the raw files other than the DNG. The arguably most exciting event was DxO finally supporting Fujifilm X-Trans files with DxO PhotoLab 5. How it works and feels can be tested with any camera. I tested PureRaw with raw format files from Canon, Fujifilm, Leica, Nikon, and the latest 60-megapixel Sony. A few exciting things happened on the X Trans demosaicing front recently. In tests with other noise reduction or sharpening programs, I often had the problem that the algorithm misinterpreted image noise as image structures. ![]()
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