The programming team behind Pixelmator Pro has just released an interesting update that introduces the ability to enhance the resolution of an image with some quite impressive results. Billed as being similar to what you often see in cheesy police dramas, the software invents detail using some sophisticated techniques.
The technology was achieved by downscaling a batch of images and then “teaching” the Pixelmator software how to upscale them back to their original resolution. As explained in this blog post, Pixelmator Pro is “predicting the values of each new pixel,” guessing the “edges, sharpness, contours, and patterns that traditional algorithms simply cannot.”
Pixelmator compares this upscaling technique to algorithms that are traditionally used to upscale images, such as Nearest Neighbour, Bilinear, and Lanczos, demonstrating the difference in quality that its ML Super Resolution offers. I decided to have a quick play myself, and the results were quite impressive.
In this test, I took a 1,920-pixel wide image and downscaled it to 800 pixels. I then resized back to 1,920 pixels using Nearest Neighbour when upscaling in Photoshop. I opened the 800-pixel file in Pixelmator Pro and repeated the process, this time upscaling it using ML Super Resolution. Click for bigger.
Pixelmator is keen to point out that the process is completely secure: “We’ve fit the entire trained model inside the Pixelmator Pro app package so all the processing is done locally and no data ever leaves the device. This is the first such tool in a consumer image editor.” Pixelmator is also emphasizing its speed and ability to remove noise and JPEG artifacts.
It certainly seems effective, and you can check out more examples in the Pixelmator blog post. What are your thoughts? Leave a comment below.