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What Is The Process Of Upscaling Of A Video/Image? How Does It Impact The Size/Quality Of An Image/Video?

Media upscaling, especially video upscaling, has significant implications for content creators. Talking about resolution, “standard definition” was the norm a few decades back. However, there are many resolution options now.

 

Resolution standards have evolved in a matter of a few years. 4K Ultra High Definition (4K UHD) devices are now a commonplace thing. The number of people using such devices has only increased in the recent past due to people being unable to go out for entertainment during the pandemic. But the problem with such high-resolution devices is that they are not suitable for viewing your favourite old SD TV shows. When played, such low resolution content might appear blurry and stretched out on your 4K UHD monitor.

 

This is where upscaling comes in. Upscaling, essentially, is the process of improving the resolution of an image or video. Now, most media consumption devices come with a built-in upscaling technology that allows you to view even low-resolution content on their high-definition displays without much difficulty. Besides, there are dedicated software tools meant for upscaling images and videos. In simple words, upscaling media has become easy, the more so, because we now have AI powered tools at our disposal.


AI enabled upscaling of images and videos
What you need to know

Over the last few years, upscaling technology has seen significant improvements, particularly with regards to Artificial Intelligence (AI). As discussed above, media upscaling refers to the process of taking low resolution media and scaling it. While increasing the resolution of a particular content is vital, it’s also important to keep as much of the original information intact as possible. In other words, the output quality should be as high as possible. 

 

The reason why upscaling is so crucial is because it can be used to preserve older media, such as films from the 20th century, old photos, and retro video games. Old photographs can be resized without any additional effort with the help of upscaling.

 

Even old media played on modern TVs and monitors will be of low quality, without upscaling. Thankfully, Artificial intelligence (AI) has dramatically increased the effectiveness of upscaling technology. With AI powered tools, upscaling media and their preservation takes very little time. 

 

AI upscaling isn’t perfect, and often requires human intervention to achieve the desired outputs, but it has surely brought great benefits to the table for both content creators and OTT service providers.

 

Note that AI upscales media with the help of certain algorithms, but there is no one-size-fits-all algorithm for this purpose. This explains why different media types require different algorithms.

Some of the most widely used AI algorithms for upscaling and how they work—

  • Interpolation to the nearest neighbor—

Nearest-neighbor interpolation is a simple way to increase image size and doesn’t require complex calculations. Hence, it offers faster results, but the quality of the output might not be as fine as those obtained with other advanced algorithms. Here, the interpolated pixels take on the values of the nearest pixels. However, nearest here doesn’t necessarily mean mathematically closest. Nearest- neighbor interpolation is a great way to preserve fine details present in an input but can also create jaggedness in images that were previously smooth. The method is relatively faster and the results generally have fewer artifacts. 

 

  • Sinc and Lanczos resampling—

This is probably the most complicated algorithm in the list. The Lanczos interpolation works like magic when it comes to preserving detail, and minimizing artifacts. The process using which it accomplishes this is complex and not easy to understand. This method produces an interpolation result similar to bicubic interpolation. The output has more of a ringed effect rather than a blurry one. Sometimes, you will see a dark or light halo along sharp edges of the rendered image. Although it may not be desired, the effect increases the perceived sharpness and clarity of an image. The Lanczos technique can be used to receive sharper and cleaner output content. Note that it is more suitable for video upscaling than still images.

 

  • Edge-directed interpolation algorithms—

These algorithms are designed to keep the edges in an image intact even after upscaling. This is unlike certain other algorithms which often cause staircase artifacts to appear.Edge-directed interpolation can be achieved using algorithms such as DCCI or Directional Cubic Convolution Interpolation, ICBI or Iterative Curvature-Based Interpolation, EGGI or Edge-Guided Image Interpolation and NEDI or New Edge-Directed Interpolation.

 

  • Bilinear algorithm—

When linear interpolation is applied in two directions, it is referred to as bilinear interpolation. It targets 4 closest pixels, and takes their weighted average for the output. It’s a great option for resizing, but causes softening of edges which might be undesirable in some cases. This method is ideal for continuous tone images. Bilinear interpolation produces significantly better results but at a higher computational cost.

 

  • Hqx—

This scaling algorithm can provide better magnifying results for computer graphics that have low resolution or fewer colors (typically between 2 and 256 colors). It can produce sharp edges and high levels of detail.

 

  • Vectorization—

Vectorization or vector extraction is another option. Vectorization first creates a resolution-independent vector representation of the graphic to be scaled. Then the resolution-independent version is rendered as a raster image at the desired resolution. A lot of upscaling software programs use this technique. 

 

  • Deep convolutional neural networks—

This technique uses machine learning to create more detailed images, such as photos and intricate artwork. This algorithm is also used by a lot of popular media scaling software tools.

 

It’s important to note here that upscaling does not apply to old footage alone. A lot of people use upscaling tools for their YouTube channels. This may be required when the videos are shot at 1080p or lower resolutions. Such renders can easily be upscaled to 4K on YouTube using upscaling tools. But why would someone do that? Well, they probably don’t own a 4K-capable camera. Besides, editing a 4K footage is not an easy task. Also, 4K footage can take up a lot of space on the drive.

 

Now, the question that arises here is— How is AI so effective in upscaling media? Well, AI learns, just like humans do. 

How does Artificial Intelligence learn to upscale?

There are patterns in images and videos which can be detected using convolutional neural networks (CNN). Images are first inserted into the input layer. Then, they are sent to hidden convolution layers that perform pattern detection with the help of filters. A filter is a matrix with random initialized values that passes over every pixel in an image. These filters are capable of identifying edges, textures, shapes and other details. The filters get more sophisticated as the image passes through more convolutional layers. They can then recognize complex structures such as vehicles or, say, animals. Once the AI has determined how to classify them, the images are passed to the output layer.

The process of upscaling videos/images—

There are third-party software programs available using which you can readily upscale videos and images. If you are an advanced user, you will find custom options to achieve the desired results on such software.

 

These apps allow you to increase the quality of your images and videos without any hassle.Make sure the software you intend to use supports your desired file format. Usually, upscaling software programs are compatible with all popular file formats.

 

You can upscale the files either automatically or manually. Most apps allow you to process files using both the techniques.You may also be able to preview the result before you save the output.

Here are some of the steps most upscaling apps need you to follow—

 

Step 1— Install the best media upscale software as per your needs—

Before choosing a software, make sure it is compatible with the operating system of your device. Once that’s done, you can download the upscaler. After downloading and installing the upscaler on your computer, open it and import the file that you wish to upscale.

 

Step 2: Increase the resolution of the file—

There are usually two ways you can upscale an image or a video—automatically or manually.

While upscaling the resolution automatically should be over with a single click on the upscale tab, manual upscaling needs the user to fiddle with the settings so as to set the desired output properties and obtain the desired results.

 

Step 3: Export the upscaled file—

Now, select your destination folder, and export the file. The video resolution will increase immediately after you hit the convert/upscale button.

 

While some apps allow you to process only one file at a time, others (more advanced ones) might allow you to process multiple videos at the same time.

 

Note that the above-mentioned are the most basic upscaling steps and different upscaling apps might execute them differently or more elaborately.

How upscaling impacts videos/ images—

Impact on the size—

When upscaling takes place, a smaller image or video gets stretched in such a way that it is able to fit the screen of the device where it appears. The main purpose is to increase the size dimensions without disturbing the quality. Upscaling is also referred to as uprezzing or upsizing. Yes, it is easier to simply scale the content according to the display size, but that will make the output appear stretched out and blurry. Hence, people use plugins and software tools to upscale media as they come with special features to eliminate issues such as noise, blur, and color artifacts. However, a higher quality image or video will by default have a very high size, and it might not be the best suited for your websites and e-catalogues. While they do give a lot of attention to detail, it is not

Impact on the quality—

Upscaling involves the use of artificial intelligence algorithms. Nowadays, these algorithms come in-built in the hardware like a Blu-ray player or a television set. Even software tools available for upscaling use algorithms for this purpose. The algorithms used are able to upscale the content using a technique called interpolation. Interpolation is nothing but guessing the best content for all the extra pixels that get added to an upscaled output. Since there is no specific data available to fill in these pixels, algorithms rely on this guessing game. While the process of upscaling can’t add detail to a piece of media, it can certainly make it appear more defined and sharper than before. So, upscaling certainly enhances the overall visual quality of the output.



Mogi Transcoding and Upscaling

Mogi I/O (www.mogiio.com) is an AI enabled Video & Image Delivery SaaS that helps Content Platforms to Improve Customer Engagement by enabling Buffer free Streaming Experience for the user through a patented multi-CDN upstream architecture called Mogi Streaming Engine, Enhanced experience through quality enhancement and compression of up to 50% both during transcoding itself and Deeper user insights through Advanced Video Analytics.

One of the best individual products we have is our Transcoding Architecture, in which upscaling and compression happen side by side, which in a unique cluster based process, does the transcoding within 30% of the content length. 

The transcoding architecture’s result includes a highly compressed video of up to 50% with no loss in quality, and if you choose quality enhancement, a 40% compression with enhanced video quality. So there are no issues of file size if you increase quality

The pricing for Transcoding is very competitive as well, and along with it you get a highly compressed output with the same or higher quality. This means not only your contractual pricing is low due to competitive pricing, your bandwidth consumption reduces, and user experiences increase multifold. It’s a win-win for all of us (Users, Clients, Mogi).

If you want to partner with us and access our products, reach out to susheel.srinivas@mogiio.com

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