Video content is growing so fast that videos occupy more than 80% of the internet traffic. The mass is actively producing and watching video content. However, the growth of the video content market has some side effects on data. It has become difficult for both the creators that produce videos and video platforms, to handle the enormous capacity of video content.
Then what will be the solution to solve this problem? That is by reducing video data. But reducing video data leads to another problem which is the loss of video quality. Therefore, we need a technology that maintains video quality but reduces capacity.
The reason for the sudden loss of YouTube video quality.
When using YouTube recently, you can notice a big difference. In the past, when you played the video, the video was played in HD quality, but now they are played in lower quality, making us change it back up to HD quality. YouTube supports up to 4K videos, but why does it play it in low-quality videos in the beginning.
The problem is because of the ‘Data issue’. The biggest video platform YouTube tried to reduce the usage, of the sudden increase of the data of video contents by, playing low-quality videos rather than high-quality videos in default. This is an example that the data issue is a serious problem affecting our daily lives.
In addition, the use of smart TVs is also demanding more use of high-quality videos. People using smart TVs enjoy contents, such as YouTube and Netflix, which need high-quality videos. Low-quality videos are more disturbing on a larger screen than on mobile, making the importance of video quality bigger. This makes it impossible for us to give up either the capacity or quality of videos.
‘PQ-optimizer’ is a cognitive image quality optimization technology that save the data rate while maintaining the quality of the video
‘PQ-optimizer’ is a cognitive image quality optimization technology that save the data rate while maintaining the quality of the video. Using self-developed AI reduces data by deleting unnecessary pixels, making it possible to reduce data without the loss of quality.
For example, when the computer we use slows down, the first thing that comes to mind is ‘data’. By erasing data, we can make our computers work faster. So we naturally check the usage of data and erase unused documents to maintain data capacity. ‘PQ-optimizer’ also follows this principle allowing users to enjoy the video with lower capacity, by erasing unnecessary pixels in the video.
One thing to notice is that the name of this technology is “cognitive image quality”. In other words, the image quality isn’t the same. But it looks the same in the human eye. Based on the VMAF score released by NETFLIX, when checking the difference from the original video the video that was applied with PQ-optimizer had scored similar. It even had a higher image quality score when using the same amount of data.
The difference ‘PQ-optimizer’ can bring in daily life.
You can see that by using ‘PQ-optimizer’ we can improve coding efficiency to reduce the capacity of videos but maintain quality, allowing us to produce more video content. Thanks to this technology we can produce and enjoy video content freely. Since it uses less data, it can also transmit high-quality videos in unstable network conditions which can be useful in live streaming.
In addition, the PQ-optimizer is a pre-processing technology that can be applied before the encoding system and because it can be applied to all codecs, it does not need the expansion of any new codecs. It can also be encoded better in the same given data and has better encoding efficiency when the quality is the same.
New creators are emerging day by day and they are producing video content actively. The mass also enjoys a lot of video content. As the amount of content is increasing tremendously, we need to prepare for the usage of data. The ‘PQ-optimizer’ introduced today will be very useful in the upcoming data issue.
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