![]() ![]() We can eliminate this extra effort with our new RAW model by utilizing the pure RAW data from the camera, where noise is ideal. Also, the RGB images can go through additional editing processes by the users, which we also account for in our RGB model training.As a result, a great deal of effort is required to cover all possible variances when using RGB models to apply noise reduction. When we train a model for RGB images, we take the variations of these RAW converters into account. Different RAW converters use varying conversion methods that change the noise pattern of the sensor data. Unfortunately, RAW converters introduce clipping, demosaicing, and other post-processing steps when converting the RAW data to an RGB image. Currently, the supported workflow requires you to convert your RAW file to a processed RGB file format that DeNoise AI uses as the input source. Let's say you want to use DeNoise AI to apply noise reduction to a RAW photo you have stored in your Adobe Lightroom Classic catalog. The degree to which this waxy look is visible always depends on the original level of noise in the original image, so less noisy images will always be more effectively resolved than those with higher noise levels.The best way to explain the benefits of the new RAW model is to compare how it works with our four existing DeNoise AI models: Standard, Clear, Low Light, and Severe Noise. And DeNoise AI certainly isn’t immune to this even at low settings. One problem with all noise reduction is the loss of detail and the ‘waxy’ appearance images can take on, strongly signifying that noise reduction has been applied. You can, of course, add more sharpening in both Lightroom and ACR to achieve a similarly sharp result. Despite this, results from DeNoise AI are generally sharper, although artefacts can appear around high contrast fine details, which makes it difficult to say whether this or Lightroom/ACR is better because both are effective yet imperfect. This makes it imperative that you try each of the three AI models to identify the best option for the image being processed. This works well for the most part but in some situations, the AI model used can result in uneven noise reduction where some luminance noise is mistaken for detail and remains visible. Where noise reduction in Lightroom and Adobe Camera Raw is applied indiscriminately across the whole image, DeNoise AI appears to apply it according to where the software identifies noise. ![]() Noise reduction can be applied to edited images saved in the most common file formats, or you can load Raw files into the software and export them as DNGs for Raw processing in your favourite software. You can opt for Auto, where DeNoise AI selects the settings it calculates are most appropriate for the image, you can go for manual control or a combination of the two. The main control panel can be found on the right-hand side of the interface and is broken up into a thumbnail and navigator, AI Model selection, setting and Post-Processing which provides additional controls for refining noise reduction before saving. ![]() Here, the Comparison View shows the original image alongside the results from the three AI Models so you can judge which is most suitable for the image you’re editing. View options include a Brighten button that lightens darker parts of the image temporarily to view noise reduction in these areas more easily, zoom allows you to zoom in and out of images, Original allows you to see the original image temporarily and the View control that allows you to change the view for comparison between the before and after. Everything is kept clutter-free with only the controls you need visible – below the main menu that you rarely need to use are several viewing controls that make results clear to see. (Image credit: James Abbot)ĭeNoise AI, like other Topaz Labs photography software, features an intuitively laid out user interface that makes removing noise incredibly easy. DeNoise AI makes it quick and easy to reduce noise in images and can result in sharper results than those possible with Lightroom and Adobe Camera Raw. ![]()
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