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Portrait Background Removal AI allows you to remove an unwanted background from your portrait in seconds thanks to AI.Layers let you effortlessly combine two or more images and manipulate them to achieve your desired effect.The AI also detects different types of lines and removes them with one click.Skylum revealed some additional features of the upcoming Luminar NEO (pre-order options: new customers | Luminar customers | Aurora customers):
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The Dust Spot Removal tool can even be used to edit images where dirt, sand or dust has gotten onto the sensor during the photo session.
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This opens up immense possibilities, from reducing edge lighting to imitating studio light. It calculates the depth of a photo and creates a depth map to spatially distribute light across a 2D image. Sky and water can also be masked simultaneously to unify color harmonies and add even more contrast. Also improved is the RelightAI tool in Luminar Neo, which works like a virtual flash for close-up portraits or group photos at events. The Enhance AI tool, for example, can be used to add accents of color, detail, depth, and tone to selected parts of the image. The Mask AI also allows you to select different objects and edit them at the same time. The artificial intelligence is so precise that it not only selects the main subject, but even distinguishes between pavement and soil. The variety of objects that can be masked with one click goes beyond people in Luminar Neo, allowing masks to be automatically created for buildings, skies, vehicles, water, mountains, and soils as well. The background removal process must first be selected, so the Portrait Background Removal tool can be found in Luminar Neo Layer's masking options. With the Portrait Background Removal feature, a slider can be used to select an object and remove the background behind it. Thanks to AI, the latest tool in Luminar Neo offers the highest accuracy. The results appear unrealistic and after the automated, another manual processing follows. Automated, web-based editing tools often do not provide the desired quality, because the selection and object detection are rather superficial.
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