• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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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.

• Journal of Korea Multimedia Society
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• v.25 no.6
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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).

• Proceedings of the Korean Information Science Society Conference
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• 1998.10a
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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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• v.4 no.6
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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.

• Proceedings of the KIEE Conference
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• 2005.10b
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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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• v.11 no.12
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.491-497
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• 2012

Network coding is that the nodes can combine and mix the packets rather than merely forward them. Therefore, network coding is expected to improve throughput and channel efficiency in the wireless network. Relevant researches have been carried out to adapt network coding to wireless multi-hop network. In this paper, we designed the network coding for bidirectional traffic service in routing layer and IP layer of Ad-hoc network. From the simulation result, the traffic load and the end to end distance effect the performance of the network coding. As end to end distance and the traffic load become larger, the gain of network coding become more increased.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.208-220
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• 2021

This paper evaluates the performance of multilayer VVC and SHVC. Multilayer VVC supports a multi-layer coding and many coding technologies have been added and extended compared to SHVC. For this reason, it is necessary to evaluate the multi-layer coding performance of VVC and the coding performance for inter-layer reference prediction. Multilayer VVC provides significant BD-rate improvement of AI 24.4%, RA 29.4%, LDB 29.4%, LDP 32.6% on average when compared to SHVC, so that it is shown that VVC can provide scalability more efficiently. On the other hand, the complexity of the encoding time increases by an average of 14 times and decoding time by an average of 1.8 times, which requires efforts to reduce the complexity.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1093-1101
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• 2012

Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding exploits inter-view correlations among pictures of neighboring views and temporal correlations among pictures of the same view. Multi-view video coding which uses many cameras requires a method to reduce the computational complexity. In this paper, we proposed an efficient prediction structure to improve performance of multi-view video coding. The proposed prediction structure exploits an average distance between the current picture and its reference pictures. The proposed prediction structure divides every GOP into several small groups to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experimental results show that the proposed prediction structure shows good performance in image quality and bit-rates. When compared to the performance of hierarchical B pictures of Fraunhofer-HHI, the proposed prediction structure achieved 0.07~0.13 (dB) of PSNR gain and was down by 6.5(Kbps) in bitrate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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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.