• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.434-442
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• 2015

In this paper, we propose an integrated spatial and view scalable video codec based on high efficiency video coding (HEVC). The proposed video codec is developed based on similarity and uniqueness between the scalable extension and 3D multi-view extension of HEVC. To improve compression efficiency using the proposed scalable multi-view video codec, inter-layer and inter-view predictions are jointly employed by using high-level syntaxes that are defined to identify view and layer information. For the inter-view and inter-layer predictions, a decoded picture buffer (DPB) management algorithm is also proposed. The inter-view and inter-layer motion predictions are integrated into a consolidated prediction by harmonizing with the temporal motion prediction of HEVC. We found that the proposed scalable multi-view codec achieves bitrate reduction of 36.1%, 31.6% and 15.8% on the top of ${\times}2$, ${\times}1.5$ parallel scalable codec and parallel multi-view codec, respectively.

• 한국멀티미디어학회논문지
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• 제25권6호
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• pp.783-792
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• 2022

Versatile Video Coding (VVC) is the latest video coding standard, which had been developed by the Joint Video Experts Team (JVET) of ITU-T Video Coding Experts Group (VCEG) and ISO/IEC Moving Picture Experts Group (MPEG) in 2020. Although VVC can provide powerful coding performance, it requires tremendous computational complexity to determine the optimal block structures during the encoding process. In this paper, we propose a fast ternary tree decision method using two neural networks with 7 nodes as input vector based on the multi-layer perceptron structure, names STH-NN and STV-NN. As a training result of neural network, the STH-NN and STV-NN achieved accuracies of 85% and 91%, respectively. Experimental results show that the proposed method reduces the encoding complexity up to 25% with unnoticeable coding loss compared to the VVC test model (VTM).

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (3)
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• pp.465-467
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• 1998

MPEG-2 는 Layered Coding방식을 채택하여 하나의 base layer와 4개의 enhancement layer로 이루어져 있으나 동영상 재생을 위해 필요한 최소한의 layer인 base layer 만으로도 데이터 양이 많기 때문에 인터넷 환경에 적용하기가 어렵다. 이에 base layer를 다시 세분화된 layer로 나누기 위해 인코딩 중에는 또는 인코딩 결과로 만들어지는 MPEG-2 Video steam 의 하부 구조인 블록층에 존재하는 8$\times$8블록의 AC 계수들을 layering한다. Layered된 base layer의 데이터는 통신망 및 단말기의 QoS에 따라 서로 다른 전송 채널을 통해 서버에서 클라이언트 디코더로 전송된 후 디코더에 실시간적으로 병합한 후 재생된다. 본 논문에서 제안하는 기법을 이용하여 기존에 encoding MPEG-2 Video steam의 AC계수를 layering할 경우에 QoS에 따라 가변적으로 데이터 양을 서버 쪽에서 조절할 수 있었고, 통신 선로 상에서 이동하는 데이터 양의 원래의 MPEG-2 Video steam 을 이용했을 때보다 인코딩 중에 블록을 변환하면 51% 정도 감소하고 인코딩 되어진 데이터를 이용했을 경우에는25%정도 감소하는 것을 알 수 있었다.

• IEIE Transactions on Smart Processing and Computing
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• 제4권6호
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• pp.422-433
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• 2015

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multi-loop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.6017-6037
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• 2017

In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

• 한국전자통신학회논문지
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• 제7권3호
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• pp.491-497
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• 2012

네트워크 코딩기법은 여러 개의 패킷을 하나의 패킷으로 압축하여 전송하는 기법으로 무선네트워크에 적용할 경우, 패킷전달횟수를 감소시킬 수 있고 채널효율성을 향상할 수 있어 관련 연구들이 활발히 이루어지고 있다. 본 논문에서는 멀티홉 Ad-hoc 네트워크에서 양방향트래픽 서비스를 위해 라우팅계층과 IP계층에 네트워크코딩기법을 적용하였다. 시뮬레이션 분석결과 트래픽부하와 종단간 홉수가 높을수록 네트워크 코딩이득이 증가하였다.

• 방송공학회논문지
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• 제26권2호
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• pp.208-220
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• 2021

본 논문은 multilayer VVC와 SHVC의 성능을 평가한다. Multilayer VVC는 다-계층 부호화 방식을 지원하며, SHVC와 비교하여 많은 기술이 추가 및 확장되었다. 이러한 이유로 VVC의 다-계층 부호화 성능과 계층 간 참조(Inter-layer reference) 예측에 대한 부호화 성능 평가가 필요하다. Multilayer VVC는 SHVC 대비 AI, RA, LDB, LDP 환경에서 각각 평균 24.4%, 29.4%, 29.4%, 32.6%의 BD-rate가 감소하는 실험 결과를 보였으며, 더 효율적으로 scalability를 제공할 수 있다는 것을 보인다. 반면 부호화 시간 복잡도는 평균 14배, 복호화 시간 복잡도는 평균 1.8배 증가하여 시간 복잡도를 줄이는 노력이 필요하다.

• 한국멀티미디어학회논문지
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• 제15권9호
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• pp.1093-1101
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• 2012

다시점 비디오는 3차원 정보를 표현하기 위한 영상으로 하나의 3차원 장면을 여러 시점에서 다수의 카메라로 촬영한 동영상이다. 영상들 사이에 존재하는 시간적 상관성과 화면간 상관성을 이용하는 다시점 비디오 부호화는 카메라의 수에 비례하여 데이터의 양이 늘어나기 때문에 계산량을 줄일 수 있는 다시점 비디오 부호화 기술이 필요하다. 본 논문에서는 다시점 비디오의 부호화 성능을 향상시키기 위한 효율적인 예측구조를 제안한다. 제안한 예측 구조는 다시점 비디오의 부호화 효율을 높이기 위하여 부호화되는 현재 화면과 현재 화면이 참조하는 참조 화면들과의 평균 거리, B계층 최대 인덱스 그리고 각 Bi 계층의 화면 수를 고려하였다. 제안한 예측 구조의 성능을 참조 예측 구조의 성능과 비교하였을 때 영상 화질 면에 있어서 제안한 예측 구조가 Fraunhofer-HHI의 계층적 B화면 구조보다 약 0.07~0.13 (dB) 성능 향상을 보였다. 발생되는 평균 초당 비트량에 있어서 제안한 예측 구조가 Fraunhofer-HHI의 계층적 B화면 구조보다 최대 6.5(Kbps) 감소하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권12호
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• pp.3018-3036
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• 2013

In this paper, we investigate power allocation scheme and outage performance for a physical-layer network coding (PNC) relay based secondary user (SU) communication in cognitive multi-antenna relay networks (CMRNs), in which two secondary transceivers exchange their information via a multi-antenna relay using PNC protocol. We propose an optimal energy-efficient power allocation (OE-PA) scheme to minimize total energy consumption per bit under the sum rate constraint and interference power threshold (IPT) constraints. A closed-form solution for optimal allocation of transmit power among the SU nodes, as well as the outage probability of the cognitive relay system, are then derived analytically and confirmed by numerical results. Numerical simulations demonstrate the PNC protocol has superiority in energy efficiency performance over conventional direct transmission protocol and Four-Time-Slot (4TS) Decode-and-Forward (DF) relay protocol, and the proposed system has the optimal outage performance when the relay is located at the center of two secondary transceivers.