How to improve video quality with artificial intelligence
Among social media users, videos are much more popular than pictures or text. With the development of the speed and quality of the Internet connection, the popularity of online content and video streaming services is growing: YouTube, Netflix, Hulu, HBO Go, Amazon Prime. Therefore, brands and individual media personalities, picking up on this trend, began to actively release visual content in high quality to meet the requirements of the audience.
What is important for the media is that images or videos in Ultra HD format can be edited without loss of picture quality. By the way, we already wrote about image enhancement technology in a previous article . But what about low-res old movies, commercials, home videos? Is it possible to improve their quality for comfortable viewing on modern screens? Let's find out.
How to improve video quality with resolution
First, let's list the most common permission types and terms. Resolution is usually given in the format width x height of the screen in pixels:
1920 x 1080: Full HD (High Definition)
2048 x 1080: 2K (Digital Cinema)
3840 x 2160: 4K (UHD - Ultra High Definition)
4096 x 2160: 4K (Digital Cinema)
7680 x 4320: 8K (UHD)
15360 x 8640: 16K (UHD)
Today, the generally accepted resolution standard is 4K, and we are moving towards 8K screens. Youtube started supporting 4K for uploading videos back in 2010, when many manufacturers started releasing inexpensive cameras in this format. Since then, 4K-enabled displays and smart TVs have dropped significantly in price and gained popularity. While the human eye can hardly physically tell the difference in a picture above 4K, the race for higher resolution continues.
The owners of Ultra HD displays can fully experience the capabilities of their screens when viewing native 4K content. And lower resolution videos have to be stretched to full screen because, for example, 1080p (Full HD) images contain only a quarter of the pixels of a 4K image. You can scale the image immediately on a smart TV, in a media player, or use special programs to improve video quality.
What can the program to improve the quality of the video?
In a nutshell, Video Enhancement is the process of enhancing the quality of a video recording. Professional video editors usually support the following features:
- scaling (upscale);
- improved lighting;
- stabilization;
- noise suppression;
- brightness adjustment;
- cropping (cropping), video rotation, mirroring;
- filters;
- effects and animation.
Video editor to improve the quality can give your old recording a second life.
Video upscaling is the process of converting lower resolution media to higher resolution. Core scaling is a way to "stretch" a lower resolution image onto a larger screen, usually with degradation in quality and loss of detail. To enlarge an HD image onto a 4K screen, an additional 6 million pixels would have to be filled in. Therefore, the upscaling program must determine what each of these new pixels will display based on what the neighboring ones show (interpolation).
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Enhance Video with AI: Super Resolution
Although different algorithms give different image quality, interpolation tends to improve low-resolution images. But the attempt to "finish" the missing pixels in most cases is striking. As a result, the image occupies the entire 4K screen, but may look washed out or muffled, or have artifacts (noise halos, squares). AI upscaling takes a completely different approach.
Given a low-resolution image, a deep learning algorithm (usually a generative neural network) predicts a higher-resolution image that, after compression, would look like our original input. To achieve this level of accuracy, neural networks must be pre-trained on millions of images. When processing low-resolution video, the AI model can “finish” the lost pixels by analyzing each frame and improving the quality exponentially. This gives you incredible clarity and detail that no traditional upscaler can recreate, from realistic detail to cleaner and smoother motion reproduction.
AI models are constantly improving and their accuracy grows with each training cycle. In addition, different deep learning models can be applied to improve different types of video content. And neural networks can also be combined: sometimes it gives amazing results.
So, artificial intelligence helped to increase the famous " Arrival of the train at La Ciotat" (L'arrivée d'un train en gare de La Ciotat) to 4K . This is a French short black and white documentary film from 1896 by the Lumiere brothers. Even though the original image was enlarged by 600%, the AI-based algorithm (DAIN and Topaz Gigapixel AI) was able to produce a sharp and clean image without visible grain, artifacts or distortion. It seems that the record is modern - only black and white.
Video processing by a neural network. Brief overview of programs
Unlike traditional (non-AI) video enhancement tools that are more complex and sometimes require professional editing skills, AI algorithms can automatically improve the quality of your videos. Here are some examples of such solutions.
DVDFab Enlarger AI - super resolution with neurons
This video enhancement service uses super resolution technology based on deep learning and can upscale videos from 480p (SD) to 1080p (Full HD), and from 1080p to 4K. A deep learning AI engine learns and analyzes low-resolution video frame by frame and can create and fill identical neighboring pixels, enlarging the frame by 300%. The program also uses intelligent color correction algorithms.
DVDFab Enlarger AI is based on the TensorFlow framework. Millions of videos, movies and TV shows have been used to train neural networks. In addition, the program uses the latest CUDA and cuDNN GPU acceleration technologies based on NVIDIA graphics cards.
PicaVue (GDFLab Video Upscaler) - Video Recovery and Resolution up to 16K
GDFLab Video Upscaler is a cloud-based video upscaling service. The developers promise to upscale video and images up to 16K by simultaneously increasing the resolution and quality:
- 270p ~ 360p to 720p or FHD;
- 540p to 4K UHD;
- 4K FHD up to 16K.
Artificial intelligence is used to eliminate noise and restore details that are not clear enough in the original image. In addition, with GDFLab Video Upscaler, you can restore old videos with a cleaner picture and better resolution. The program can be used for video from surveillance cameras, filming, social networks, as well as in any field related to video recording. Users can upload their images and videos simultaneously to all major platforms: YouTube, Facebook, LinkedIn, Twitch and more.
Topaz Video Enhance AI - realistic details generated by a neural network
We mentioned this video editor when we wrote about restoring an 1896 documentary to 4K. Topaz Video Enhance AI is considered one of the best video enhancement software. It can upscale up to 8K while maintaining realistic detail and smooth motion.
Video Enhance AI can upscale DVDs, DSLRs, games and HD. You can also upgrade older videos for modern use, such as commercials, music videos, movies, or YouTube recordings.
Topaz Video Enhance AI uses deep learning to extrapolate details from video footage. It works on the basis of neural network training: it analyzes thousands of video pairs to determine how image details are lost during compression. The neural network can generate the missing details and create a realistic picture based on information from a single video.
Instead of output
Zooming in and enhancing video with AI creates an effect that can perhaps be compared to the sensations of a myopic person wearing glasses: it turns out that the world is full of details, trees have leaves, and road signs, signs and bus numbers can be easily read. At the moment, Full HD and 4K are still the most popular resolution formats for watching videos on the Internet and on TV, but the upper limit of picture quality has not yet been set.
The Evergreen team has years of experience using TensorFlow, an open source machine learning framework, to build and implement AI-powered projects in many business areas.
We specialize in developing personalized solutions for clients and can build an MVP (Minimum Viable Product) quickly and cost-effectively, which can be developed and scaled into a full-fledged product in the future.
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