In a blog post today, Pixelmator Pro launched ML Super Resolution, a machine learning-based technology that allows users to increase the scale and size of an image, without the typical blurriness that comes along with it.
In the post, Pixelmator says:
Our latest ML-powered feature is called ML Super Resolution, released in today’s update, and it makes it possible to increase the resolution of images while keeping them stunningly sharp and detailed. Yes, zooming and enhancing images like they do in all those cheesy police dramas is now a reality!
In comparison to the current technology which is just simply based on mathematical calculations of pixels, let’s look at some examples:
The post also dives deep into how the technology works, highlighting the difference between the current technology, and ML:
As computers get ever more powerful, the additional power opens up new possibilities. One of the uses of machine learning, on a very fundamental level, is to make predictions about things. In this case, we gathered a set of images, scaled them down, and then ‘taught’ the algorithm to go from the scaled-down version to the original resolution, high-quality image, predicting the values of each new pixel. The algorithm can’t recreate detail that is too small to be visible but it can make amazing predictions about edges, shapes, contours, and patterns that traditional algorithms simply cannot.