Upscaling software is getting better all the time, but there are still some caveats to be aware of.
The shift from analogue film to digital video happened quickly. Before you knew it, tape-based video recorders had been replaced with digital video cameras and, later still, smartphones. 4K is now the gold standard for video creation, with 1080p left as its lower-quality sibling.
Despite widespread 4K adoption, there’s still plenty of video being created in 1080p. And that’s not to mention content made in the past, from home videos to old movies, available in standard definition or even lower. That can lead you to thinking about converting video to 4K, giving it a boost to make it look as sharp on a modern 4K OLED display as something you’d shoot today. Converting a video to 4K is possible, but it’s a process with a lot of steps and points to consider first.
Converting a video to 4K means creating millions of new pixels
When we talk about 4K and 1080p, or ultra-high and high definition, we’re talking about the amount of pixels contained within each video frame. For ultra-high definition video content, which is what most people usually mean by 4K,
, versus 1,920 x 1,080 pixels for 1080p high definition video. Standard definition video, meanwhile, sits at either 480 or 576 vertical lines depending on your region; width can vary depending on how the content was originally filmed. You can
, so-called ‘true 4K’ or DCI 4K, with a resolution of 4,096 x 2,160.
You can upscale any output file to 4K — 4K is just the frame size. To move from 1080p to 4K, you’re going to need three additional pixels on-screen for every original pixel that was recorded, so four times overall. Managing that without losing any quality is the issue. That is almost impossible and simply changing the resolution won’t reveal a hidden version with extra clarity or sharpness, either.
to manage this, scaling up each frame and figuring out what it should look like. How accurate upscaling software can be is the main question. It has to estimate what the pixels should look like, but it can’t recover the real detail if it wasn’t recorded in the first place.
Often, this means that sizing up will make the footage look softer. The “guess-timation” used to add extra pixels often makes it look smooth as a result. Sharpening can help around the edges, but it’s a Goldilocks dilemma: too much, or not enough, can ruin it. The same is true for
Professional 4K restorations often return to high-quality original source files
If you’re a professional looking to convert a video to 4K, you’re going to want to work from the best source data available to you: the original source files. The better that source data is, the better quality a job you’ll be able to achieve.
proves how tricky this can be if you want to get the process right. That upgrade, commissioned by CBS in 2011, used the show’s original 35mm film negatives, which were described as having a
, to remaster all seven seasons of the show from their original broadcast quality to 1080p for Blu-ray release. 25,000 reels of original film stock were used, with visual effects and CGI upgrades to help the process. It took over three years to complete and reportedly cost the studio over $12 million,
Ironically enough, the analog film to digital video conversion here makes this type of job easier. If you’re working with an older digital master file with a set resolution, you’re stuck with a fixed number of pixels to work from. The original negatives used in the
upgrade capture far more detail that wouldn’t have made it into the original television broadcasts.
Unfortunately, when the best source files are already low resolution, you’re not able to work from the real data. All of the missing pixels that are created are guesses. The best result is that this will look pretty convincing, but it won’t be 100 percent true to form.
Home upscaling uses interpolation or AI to fill in the gaps
Unlike CBS, you’re unlikely to have $12 million to convert your videos to 4K. Home users converting video to 4K will instead have to choose between traditional interpolation or newer AI-based tools. Both methods will create the additional pixels needed to fill out an enlarged 4K frame, but not in the same way.
4K upscalers using interpolation rely on good, old-fashioned math. It takes a pixel from a single frame and looks at the color and brightness of the pixels around it. From there, it’ll try to
. At a basic level, it might achieve this by sheer duplication, but more advanced algorithms will focus on trying to preserve edges and avoid jagged lines. The end result is pretty predictable, but one problem is softness. Interpolation can’t magically recreate genuine detail or textures, making it seem slightly fake. Your TV
Luckily, AI upscaling looks to solve that problem. These models are
trained on examples of low and high-resolution images
that allow it to identify how common features should look on your screen. Inst