Professor Munchurl Kim, developed real-time full HD video 4K UHD conversion technology by artificial intelligence

Professor Munchurl Kim of our department developed a technology that can convert full HD video into super-high definition 4K UHD video using deep learning technology.

This technology has been implemented in hardware by Deep Convolution Neural Network (DNCC), which is a key techonology in artificial intelligence. It is expected to contribute premium UHD TV, 360 VR, and 4K IPTV in the future by developing algorithms and hardware that can create ultra high resolution 4K UHD screen in 60 frames per second in real time.

This study was lead by Yongwoo Kim and Jae-Seok Choi Ph.D. candidates and they are preparing for patent application.

In recent years, efforts have been made to apply Deep Convolutional Neural Network (DNCC) on image quality improvement research. However, Deep Convolutional Neural Network (DNCC) technology has a high computational complexity, and there is a limit to real-time conversion to ultrahigh-resolution images through small hardware because it needs large memory.

In the conventional frame-by-frame image processing method, it is necessary to use external memory such as DRAM, which causes memory bottleneck and power comsumption due to excessive external memory access when processing image data.

Professor Kim's team developed an efficient Deep Convolution Neural Network structure that can process data in units of lines instead of frames to implement 4K UHD super resolution at 60 frames per second on small hardware without using external memory.

His team maintained a similar picture quality with only 65% of the filter parameters compared to the fast algorithm based on deep convolution neural networks and software.

This is the first example to implement 60 frames per second 4K UHD super resolution by using hardware.

Professor Kim said, "This research is a very important example of the Deep Convolutional Neural Network that is practically applicable to ultra-high-quality image processing in small hardware. Currently, it can be applied to premium UHD TV and UHD broadcast contents, 360 VR contents, 4K IPTV services."  

This research was carrier out with the support from the Institute for Information & communications Technology Promotion


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