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How Does an AI Upscale an Image? AI Upscaling Defined

February 10, 2023 - Revolutionized Team

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Have you ever heard of AI upscale image?

Since its introduction, artificial intelligence (AI) has significantly changed many industries, including some you might not expect. AI technology uses the digital equivalent of neurons to process data and deliver conclusions that weren’t possible with conventional computing. The result is a far grander range of prediction and interpretation capabilities for modern software.

One of the most interesting AI applications in the software realm is known as AI image upscaling. We’re here to answer your questions about it, including:

What is an AI image upscale? How does it work? And, most importantly, why is it worth talking about?

What Is AI Upscaling?

Image upscaling existed before artificial intelligence. However, AI has the potential to upscale images far faster and more effectively than some human graphic artists can accomplish. But what is the image upscaling process?

AI upscaling refers to the process using artificial intelligence algorithms to increase the native resolution of an image or a video. This creates a sharper, high-def version of the original media.

For example – you might upscale an image measuring 940 x 940 pixels and create a 1440 x 1440 version instead. For video, you could begin with a resolution of 1280 x 720 (720p) and use editing software to upscale it to 2560 x 1440 (1440p).

How Does AI Upscale an Image?

With the definition of image upscaling understood, the next question is: What does AI bring to the table? How does an AI go about upscaling a video or still image, and why is it better than a human at doing so?

As mentioned, AI uses simulated neurons – a “neural net” – to process data faster than conventional computers and generate more valuable conclusions. AI can even approximate human creative expression, which is the basis of today’s conversation. It’s possible to upscale images and videos by hand, but the process is charitably referred to as “painstaking.”

AI image upscaling straddles the line between pure analytical processing and creative expression. Some of the more funny-looking upscaling results look decidedly like the result of rigid digital thinking. But, as we’ll see, such AI processes only become more sophisticated over time and better at their jobs.

Upscaling Algorithms

There are several algorithms available to professionals and general consumers. Some image and editing software platforms even offer a choice between several of the available algorithms, including:

  • Bicubic
  • Bilinear
  • ESRGAN
  • Gigapixel AI
  • Lanczos
  • Nearest Neighbor
  • Nvidia Gameworks
  • SFTGAN
  • Sharpen AI

Although all of these algorithms serve the same basic utilitarian function – increase the resolution of an image – they all go about it in a slightly different way. One algorithm may prioritize sharpening the image, while another one might be better at removing digital “noise” from the picture. It’s possible to take a single image and get two different results by feeding it through two different algorithms.

Moreover, the “thought” processes churning under the hood of an AI are the result of feeding that AI as much training data as possible. As additional image-focused AI products come to market, they’ll all interpret and process the provided image in different ways depending on the body of training data available to the AI developer.

Interpolation

At its core, AI image upscaling leans on a single principle:

Interpolation.

If you want to take an image or video of a certain resolution – with two fixed dimensions – and “blow it up” so it’s a larger image (some software calls this “super-resolution”), there are going to be “gaps” between pixel data, for lack of a better term.

In other words, maintaining the same sharpness and level of detail at a higher resolution without the final image looking blurry isn’t possible without interpolation. This is the process of “filling in” the missing pixel data with best-guess data generated by the AI.

This is where all of that training data comes in handy. An AI trained on a very wide variety of data can make better guesses about what to insert into the areas of the image that require additional data to look crisp, sharp, and consistent with both the original image and with real life. As it fills in the missing image data, imagine the AI “asking” itself “questions” about:

  • Skin tone and surface detail
  • Material textures
  • Continuity and accuracy of shadows and highlights
  • General color consistency
  • Shifting of focus between the background and foreground

Do people need to get involved with this process at all for it to work? This brings another question to mind:

Are Humans Still Needed in the AI Image Upscale Process?

The short answer is yes.

Although the bulk of the labor may be performed by an AI, the above points prove that human intuition is still required to achieve the best results. A human must study the raw material first – be it a single still image or a feature-length motion picture – and choose an appropriate algorithm to work on that substrate.

It might require a graphic design expert’s trained eye to identify what kind of artifacting and digital noise the original image might yield during upscaling. AI is a tool, and like any tool, a person is required to choose the right one for the job at hand.

What Might the Future of AI Image Upscaling Look Like?

In the future, image-upscaling AI will likely become even more capable as their collections of training data grow larger. Additional innovation and iteration may produce an all-purpose image-processing AI that can determine without human input what kind of algorithm is required to achieve optimal results.

It’s somewhat more likely, however, that the pressures of market-based competition will continue to produce a range of AI image-editing software with different niches, focuses, capabilities, and quality levels. Given the sheer breadth of possible artistic expression in the visual arts, that may end up being a good thing.

How Can I Upscale My Images for Free?

Professionals and anyone hoping to get the best results from their AI image upscaling projects would do well to consider paying for professional-grade software. It’s still a fairly novel concept to have AI products involved with graphic design at all, but that doesn’t mean various companies haven’t been busy getting their own products to market as quickly as possible.

The two most mature and capable products in the AI image upscaling software category are generally considered to be:

  • Cupscale (Free)
  • Topaz Video Enhance AI (Free trial; one-time purchase of $200)

Cupscale features a full AI tool kit for hobbyists, experimenters, and even some professionals to dig into and play with. It doesn’t support every file type that Topaz does, doesn’t have some of the user interface (UI) refinements, and it’s a little slower during processing, but it’s still fully capable of running multiple algorithms to upscale images and videos.

Anyone who’s interested in giving this class of software a spin has several other paid and free options available as well. Each one provides a different quality of result:

  • Video2x (Free)
  • AVCLabs Video Enhancer AI ($39.99/month)
  • DVDFab Video Enhancer ($$59.99/month)

As you can see, there’s something for everybody, whether you just want to give the concept a try, or it’s part of your job to explore ways to enhance digital media for broadcast or publication.

Why Is AI Upscaling Worth Talking About?

AI continues to deliver.

There seems no limit to the possible applications, benefits, and even creative expression that AI is capable of. A 2020 survey from PwC confirms that AI has fully gone mainstream, with 86% of organizations considering it a mature business technology.

It’s worth talking about in the context of entertainment and image processing for many reasons, one of which is the relentless crawl of time. Human beings value history, myth, and storytelling – and in some cases, it’s a battle against time to preserve artistic expression committed to certain mediums, like tape and non-digital photography.

As the number of screens in our world grows ever larger and their resolutions ever sharper, AI can help us continue to enjoy older films, photos, and TV shows. The upscaled re-releases of Charlton Heston’s “The Ten Commandments” and Gene Roddenberry’s “Star Trek: The Next Generation” look like they could’ve been filmed just yesterday. Thanks to upscaling, new generations of movie and TV show fans will get to enjoy these products according to their artistic merit and not the limits of their chosen medium.

Whether for creativity or pure business success, AI is here to stay and is helping us deliver better decisions and results – and even better-looking artistic works.

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