Neural network-based video preprocessing techniques have recently shown remarkable improvements in video codec performance. However, conventional preprocessing methods tend to prioritize perceptual quality over peak signal-to-noise ratio (PSNR), a key standard for video quality assessment. In this study, We propose a novel deep preprocessing method based on a group of pictures (GOP) structure, specifically aimed at enhancing the rate-distortion performance in terms of PSNR. This approach involves developing a video compression model that employs the GOP structure of the target video codec and training a preprocessing model through joint optimization with the video compression model. Experimental results demonstrate that our GOP-based deep preprocessing method not only improves PSNR but also elevates other quality metrics, including VMAF, across various codecs like MPEG-2, HEVC, and VVC. Additionally, ablation studies highlight the critical role of GOP structures in enhancing encoding efficiency based on PSNR.

This study investigates the practical performance of neural-network post-filters standardized in ITU-T H.274. We implement neural-network models on a Field-Programmable Gate Array (FPGA), allowing real-time processing of 4K 60fps encoded videos transmitted via 12G-SDI. Experimental results suggest that a minor bitrate increase for the transmission of the neural-network model weights can enhance the quality of the videos encoded by Versatile Video Coding (VVC).

This paper studies the video bit-rate required for 8K 119.88 Hz (120 Hz) high efficiency video coding (HEVC)/H.265 temporal scalable coding that can partially decode 59.94 Hz (60 Hz) video frames from compressed 120 Hz bit-streams. We compress 8K 120 Hz test sequences using software that emulates our developing HEVC/H.265 encoder and conduct two types of subjective evaluation experiments to investigate the appropriate bit-rate for both 8K 120 and 60 Hz videos for broadcasting purpose. From the results of the experiments, we conclude that the required video bit-rate for 8K 120 Hz temporal scalable coding is estimated to be between 85 and 110 Mbps, which is equivalent to the practical bit-rate for 8K 60 Hz videos, and the appropriate bitrate allocation for the 8K 60 Hz video in 8K 120 Hz temporal scalable video coding at 85 Mbps is presumed to be ~80 Mbps.

In this study, we verify a pair comparison method in which videos being evaluated can be repeated by the evaluators as many times as desired. We use the method to conduct a subjective evaluation of 8K 119.88 Hz (120 Hz) and 59.94 Hz (60 Hz) videos that were compressed using software that emulates an 8K 120 Hz encoder. The experimental results confirm that (1) this method can detect small differences between video qualities, (2) all video pairs must be evaluated because the order effect is not negligible, and (3) the appropriate number of repeats is between four and nine.

This paper describes a hardware implementation of HEVC (High Efficiency Video Coding) video encoder for exploring performance of HEVC in real-time applications. By optimizing hardware architecture and developing fast mode decision algorithms, our FPGA-based prototype can encode 1080p, 10-bit video at 60fps in real-time. Both objective and subjective evaluations clearly demonstrate that the developed HEVC encoder achieves significant coding gain relative to professional-use AVC/H.264 encoder available on the market. This paper also refers to the development of a real-time HEVC encoder for much higher resolution video such as SHV (Super Hi-Vision, 8K) using the HD encoder in parallel.

To help pave the way for Super Hi-Vision (SHV) broadcasting, we have developed a new codec system that can encode and decode SHV signals in real time. This is the third generation of SHV real-time hardware codec. This efficient compression system maintains high picture quality by using eight 1080/60p (60 frames/s) encoding units and a video format converter with signal compensation processing that takes the properties of the Dual Green format of SHV into account. The video format converter divides an SHV image spatially into eight 1920 × 1080 portions, each of which is fed to the encoding unit. In the previous SHV codec, the SHV image was divided into 16 portions (spatially eight and temporally two) and 16 1080/30p encoding units were used. Compared with the previous system, the new codec achieves a 50% bitrate saving and downsizes the codec by almost half. Furthermore, several new technologies were developed and installed in the codec. We conducted the world's first SHV international transmission over an advanced Internet connection using the codec at a TS rate of 260 Mb/s. The received picture quality was good enough to show any kind of SHV content on a large screen.

Bit-depth scalable coding method is an approach that generates multiplexed bit-streams that can be decoded to two video sequences, for Standard Dynamic Range (SDR) environment and for High Dynamic Range (HDR) environment. This paper presents a bit-depth scalable coding method that is considered as gradation restoration in interlayer prediction process. Our proposed inter-layer prediction uses a histogram interpolation method that enables to generate more mid-gray brightness levels than traditional inverse tone mapping methods with one-to-one correspondence.

We propose a novel video coding scheme targeting Super Hi-Vision (SHV) video sources. While it takes a conventional block-based MC + Transform hybrid coding approach that is suitable for hardware implementation of a SHV video codec, the proposed scheme achieved significant coding efficiency improvement by introducing several coding tools such as intra prediction and adaptive transform. According to our experimental analysis, the proposed scheme achieves significant bit-rate saving compared to the state-of-the-art AVC/H.264 high profile.

This paper presents a denoising method of intra-coded pictures using motion estimation and pixel shift. Firstly, we show that pixel-aligned mixture of distorted images which are spatially shifted and differently encoded brings reduction of quantization errors. We show that this effect can be formulated as a special case of Wiener-Hopf equation and independence of quantization errors affects the performance. We then consider its application to denoising of intra-coded pictures by using motion estimation and pixel shift. Experiments using actual image sequences verify that motion estimation is effective in moving regions, pixel shift is effective in static regions and favorable PSNR gains are achieved.

The Super Hi-Vision (SHV) developed by NHK is an ultrahigh-definition video system with 4000 scanning lines. Its video format comprises 7,680×4,320 pixels, which is 16 times the total number of pixels of HDTV (High Definition Television) and the frame rate is 60 Hz with progressive scanning. It has been designed to give viewers a strong sense of reality. In order to make the system suitable for practical use such as broadcasting services, a high-efficiency compression coding system is necessary. Therefore, we have developed several Super Hi-Vision codec systems based on MPEG-2 and AVC/H.264 video coding standards. SHV video signals are converted to sixteen HDTV signals and each video signal is processed by HDTV codec. The codec systems share some characteristics such as the frame synchronized encoding function. In this paper, details of these codec systems are described and transmission experiments using the codec are introduced.