Adobe gives Lightroom a boost with Sensei-powered functionality

Adobe Lightroom Targeted Adjustment Tool and ad hoc photo sharing feature.
Image credit: Adobe

Adobe has announced an update to its Lightroom CC, Lightroom Classic and Camera Raw applications, the highlight being a new feature, powered by its Sensei AI, called Enhance Details.

Adobe claims the new feature harnesses the power of machine learning and computational photography, with its ultimate purpose being to increase resolution in images by up to 30%.

This is thanks to a revised method of demosaicing images, which is the process raw files from most cameras undergo in order to establish red, green and blue values at every pixel.

The company reckons this is effective on images regardless of whether they’ve originated from a camera with a Bayer RGB color filter array or one of the X-Trans CMOS sensors found inside the majority of current Fujifilm cameras. A white paper released by the company goes into further details.

Histogram clipping indicators. Credit: Adobe

Histogram clipping indicators. Credit: Adobe

Other functions that arrive in this most recent update include HDR, Pano and HDR Pano Merge tools, while users of Lightroom CC will also benefit from histogram clipping indicators (above), as well as a new Targeted Adjustment Tool. This is said to provide better control over color and tonality when editing images, and appears to allow for control over settings such as hue, saturation and luminance in specific parts of the image without the need for a selection to be made first.

Meanwhile, Nikon users who tether their cameras to their computers in conjunction with Lightroom Classic CC are also promised improved performance stability. The updates also bring a number of bug fixes, while adding support for raw files from recent cameras and lens profiles for recently released optics.

Those using Adobe Lightroom on iOS devices will also now be able to take advantage of a new ad-hoc sharing feature, which allows for an arbitrary selection of images to be quickly selected and shared online, without them needing to be placed into a separate album.