• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2009-2014
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• 2007

A novel method of minimizing video quality variation is proposed for a real-time frame-layer rate control algorithm with a transmission buffer. The proposed rate control method uses a non-iterative optimization method for low computational complexity, and performs bit allocation at the frame level to minimize variation in distortion between frames. In order to reflect the buffer status, we use well-known PID control method. Computational complexity of PID control is very low, so the proposed algorithm is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better PSNR performance than the existing rate control method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.11-19
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• 2006

The recent video coding standard H.264 employs the rate-distortion optimization (RDO) method for choosing the best coding mode; however, it causes a large amount of encoding time. Thus, in order to reduce the encoding time, we need a fast mode decision algorithm. In this paper, we propose a fast inter mode decision algorithm considering quantization parameter (QP). The occurrence of best modes depends on QP. In order to reflect these characteristics, we consider the coded block pattern (CBP) which has 0 value when all quantized discrete cosine transform (DCT) coefficients are zero. We also use the early SKIP mode decision and early $16{\times}16$ mode decision methods. By computer simulations, we have verified that the proposed algorithm requires less encoding time than the fast inter mode decision method of the H.264 reference software for the Baseline and Main profiles by 19.6% and 18.8%, respectively.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.223-236
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• 2012

We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.697-702
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• 2010

Contour artifact is known as the unintentional result of quantizing a flat area that has smooth gradients. In this letter, a decontouring algorithm is proposed to efficiently remove false contours that occur in typical block-based video coding applications. First, the algorithm goes through a refinement stage to determine candidate blocks probably having noticeable false contours with different kinds of features in a block. Then, pseudo-random noise masking is applied to those blocks to mitigate the contour artifacts. This block-based selective decontouring can efficiently remove the unnecessary processing of those blocks that have no false contour, which incidentally ensures a minor penalty in visual quality and computational complexity. The proposed algorithm was demonstrated, integrated into H.264/AVC, that visual quality can be significantly enhanced with an ignorable rate-distortion (RD) loss and an minor increase in computational complexity.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.89-96
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• 2016

The High Efficiency Video Coding (MPEG-H HEVC/ITU-T H.265) is the newest video coding standard which has the quadtree-structured coding unit (CU). The quadtree-structure splits a CU adaptively, and its optimum CU depth can be determined by rate-distortion optimization. Such HEVC encoding requires very high computational complexity for CU depth decision. Motivated that the blob detection, which is a well-known algorithm in computer vision, detects keypoints in pictures and decision of CU depth needs to consider high frequency energy distribution, in this paper, we propose to utilize these keypoints for fast CU depth decision. Experimental results show that 20% encoding time can be saved with only slightly increasing BDBR by 0.45% on all intra case.

• MALSORI
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• no.66
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• pp.73-86
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• 2008

Beamforming is one of the spatial filtering techniques which extract only desired signals from noisy environments using microphone arrays. Fixed beamforming is a simple concept and easy to implement. However, it does not show good performance in real noisy conditions. As an adaptive beamforming, Frost algorithm can be a good candidate. It uses the concept of the linearly constrained minimum variance (LCMV) algorithm. The difference between the Frost and the LCMV algorithm is the error correction scheme which is very effective feature in the aspect of performance. In this paper, as quadrature mirror filtering (QMF)-based filterbank is utilized as the pre-processing of the Frost beamformning, the filter length and the learning rate of each band is optimized to improve the performance. The performance is measured by the signal-to-noise ratio (SNR) and the Bark's scale spectral distortion (BSD).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.197-199
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• 2014

현재 MPEG에서 표준화 중인 IVC(Internet Video Coding)에서는 기존의 비디오 부호화 표준과 같이 Lagrange 계수 기반의 율-왜곡 최적화(RDO: Rate-Distortion Optimization)를 사용하여 최적의 부호화 모드를 결정하고 있다. RDO를 위하여 픽쳐 타입과 부호화 구조에 따라 미리 결정된 Lagrange 계수가 선택적으로 사용되고 있다. 한편 IVC에서는 저지연 모드 부호화 구조에서 비참조 P 프레임 부호화 기법을 선택적으로 사용하여 상당한 부호화 성능을 얻고 있다. 하지만 Lagrange 계수 선택에서 기존의 P 프레임과는 다른 비참조 P 프레임의 RD 특성이 반영되고 있지 않다. 본 논문에서는 비참조 P 프레임의 RD 특성을 고려하여 기존의 기법을 확장한 새로운 Lagrange 계수 선택 기법을 제안한다. 실험결과 제안기법은 IVC 시험모델 ITM 10.0에서 기존 기법 대비 0.4%의 비트율 감소를 얻을 수 있음을 확인하였다.

• ETRI Journal
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• v.28 no.4
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• pp.425-434
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• 2006

We propose a fast macroblock mode prediction and decision algorithm based on contextual information for Pslices in the H.264/AVC video standard, in which the mode prediction part is composed of intra and inter modes. There are nine $4{\times}4$ and four $16{\times}16$ modes in the intra mode prediction, and seven block types exist for the best coding gain based on rate-distortion optimization. This scheme gives rise to exhaustive computations (search) in the coding procedure. To overcome this problem, a fast inter mode prediction scheme is applied that uses contextual mode information for P-slices. We verify the performance of the proposed scheme through a comparative analysis of experimental results. The suggested mode search procedure increased more than 57% in speed compared to a full mode search and more than 20% compared to the other methods.

• ETRI Journal
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• v.34 no.1
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• pp.106-109
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• 2012

In this letter, we propose a new prediction block filter that can reduce errors between the original and prediction blocks. The proposed filter adaptively adjusts filter coefficients by using the previously reconstructed adjacent blocks and their prediction blocks. Then, the filter is selectively applied to the current prediction block according to the rate-distortion optimization. Moreover, since the same filter coefficients can be derived in the decoder, they are not encoded into the bit-stream. The proposed method achieves a 4.65% bitrate saving on average compared with H.264/AVC.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.14-29
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• 2020

The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.