• Title/Summary/Keyword: Optimal Broadcast

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Efficient Video Streaming Mechanism through a New Rate Adaptation Scheme (새로운 전송률 적응기법을 통한 효율적인 비디오 스트림 전송 메커니즘)

  • Lee, Sun-Hun;Chung, Kwang-Sue
    • Journal of Broadcast Engineering
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    • v.14 no.1
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    • pp.44-58
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    • 2009
  • To provide efficient video streaming service over a wireless networks, the rate adaptation scheme should be applied at the low layer and the quality adaptation scheme should be considered at the high layer. In this paper, we propose a new cross-layer design which includes rate adaptation scheme at the MAC/PHY layers and quality control at the application layer. Proposed rate adaptation scheme improves the wireless channel utilization by transmitting the consecutive frames and selects optimal transmission mode by calculating the goodputs for each transmission mode. Based on selected transmission mode, the rate adaptation scheme calculates the rate limits and informs that to the application layer. Then the video streaming application utilizes this rate limits to adjust the quality of the video stream. Through performance evaluations, we prove that our cross-layer design improves the quality of the wireless video streaming service by means of the proposed rate adaptation scheme.

Digital Hologram Encryption Algorithm using Fresnel Diffraction (프레넬 회절을 이용한 디지털 홀로그램 암호화 알고리즘)

  • Lee, Yoon-Hyuk;Seo, Young-Ho;Kim, Dong-Wook
    • Journal of Broadcast Engineering
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    • v.20 no.6
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    • pp.807-817
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    • 2015
  • This paper is to propose an encryption method for only an allowed user to see the content for a digital hologram, that is a high value-added content. This paper uses a characteristic of Fresnel transform that the object region is concentrated to a relatively small part of the diffraction plane. By encrypting the concentrated part only the region to be encrypted and in turn the amount of data to be encrypted is reduced a lot, which results in an high efficiency with low encryption rate. As the methodology, a digital hologram is first Fresnel transformed for reconstruction and the result is secondly Fresnel transformed to concentrate the energy into the center of the diffraction plane to encrypt the concentrated region only. For the 2nd transform, energy concentration degree is determined by adjusting the diffraction distance and encryption strength is determined by adjusting the scaling factor. For this we analyze the optimal encryption area according to the diffraction distance and the scaling factor. When applying the proposed method with diffraction distance of 20m the object information was visually unrecognizable with the encryption ratio only 0.005% ~ 0.02%.

Complexity Balancing for Distributed Video Coding Based on Entropy Coding (엔트로피 코딩 기반의 분산 비디오 코딩을 위한 블록 기반 복잡도 분배)

  • Yoo, Sung-Eun;Min, Kyung-Yeon;Sim, Dong-Gyu
    • Journal of Broadcast Engineering
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    • v.16 no.1
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    • pp.133-143
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    • 2011
  • In this paper, a complexity-balancing algorithm is proposed for distributed video coding based on entropy coding. In order to reduce complexity of DVC-based decoders, the proposed method employs an entropy coder instead of channel coders and the complexity-balancing method is designed to improve RD performance with minimal computational complexity. The proposed method performs motion estimation in the decoder side and transmits the estimated motion vectors to the encoder. The proposed encoder can perform more accurate refinement using the transmitted motion vectors from the decoder. During the motion refinement, the optimal predicted motion vectors are decided by the received motion vector and the predicted motion vectors and complexity load of block is allocated by adjusting the search range based on the difference between the received motion vector and the predicted motion vectors. The computational complexity of the proposed encoder is decreased 11.9% compared to the H.264/AVC encoder and that of the proposed decoder are reduced 99% compared to the conventional DVC decoder.

Binary Mask Estimation using Training-based SNR Estimation for Improving Speech Intelligibility (음성 명료도 향상을 위한 학습 기반의 신호 대 잡음 비 추정을 이용한 이산 마스크 추정 방법)

  • Kim, Gibak
    • Journal of Broadcast Engineering
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    • v.17 no.6
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    • pp.1061-1068
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    • 2012
  • This paper deals with a noise reduction algorithm which uses the binary masking approach in the time-frequency domain to improve speech intelligibility. In the binary masking approach, the noise-corrupted speech is decomposed into time-frequency units. Noise-dominant time-frequency units are removed by setting the corresponding binary masks as "0"s and target-dominant units are retained untouched by assigning mask "1"s. We propose a binary mask estimation by comparing the local signal-to-noise ratio (SNR) to a threshold. The local SNR is estimated by a training-based approach. An optimal threshold is proposed, which is obtained from observing the distribution of the training database. The proposed method is evaluated by normal-hearing subjects and the intelligibility scores are computed by counting the number of words correctly recognized.

Complexity Reduction of HEVC SAO Intra Modes By Adjustment of Offset Values (HEVC SAO 인트라 모드 오프셋 값 조정을 통한 복잡도 감소)

  • Mun, Ji-Hun;Choi, Jung-Ah;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.19 no.3
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    • pp.355-361
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    • 2014
  • In this paper, we propose a complexity reduction method of sample adaptive offset (SAO), which is an in-loop filter in high-efficiency video coding (HEVC). In the conventional SAO, an offset value is calculated for each coding tree block (CTB) to minimize the error between the original and reconstructed images. In order to determine the optimal offset value, all offset candidates are examined and the offset value that leads to the smallest rate-distortion cost is chosen. Thus, SAO occupies a significant amount of the computational complexity in the HEVC encoder. In the proposed method, we determine the least-used band (LUB) by considering the statistical characteristics of offset values and without processing the offset value included in the LUB. Also, in the offset value decision stage, we check only a certain number of candidates rather than all of them. Experimental results show that the proposed method reduces the encoding time by approximately 8.15% without yielding a significant loss in terms of coding efficiency.

Combined Normalized and Offset Min-Sum Algorithm for Low-Density Parity-Check Codes (LDPC 부호의 복호를 위한 정규화와 오프셋이 조합된 최소-합 알고리즘)

  • Lee, Hee-ran;Yun, In-Woo;Kim, Joon Tae
    • Journal of Broadcast Engineering
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    • v.25 no.1
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    • pp.36-47
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    • 2020
  • The improved belief-propagation-based algorithms, such as normalized min-sum algorithm (NMSA) or offset min-sum algorithm (OMSA), are widely used to decode LDPC(Low-Density Parity-Check) codes because they are less computationally complex and work well even at low SNR(Signal-to-Noise Ratio). However, these algorithms work well only when an appropriate normalization factor or offset value is used. A new method that uses a CMD(Check Node Message Distribution) chart and least-square method, which has been recently proposed, has advantages on computational complexity over other approaches to get optimal coefficients. Furthermore, this method can be used to derive coefficients for each iteration. In this paper, we apply this method and propose an algorithm to derive a combination of normalization factor and offset value for a combined normalized and offset min-sum algorithm to further improve the decoding of LDPC codes. Simulations on the next-generation broadcasting standards, ATSC 3.0 LDPC codes, prove that a combined normalized and offset min-sum algorithm which takes the proposed coefficients as correction coefficients shows the best BER performance among other decoding algorithms.

Facial Expression Classification Using Deep Convolutional Neural Network (깊은 Convolutional Neural Network를 이용한 얼굴표정 분류 기법)

  • Choi, In-kyu;Song, Hyok;Lee, Sangyong;Yoo, Jisang
    • Journal of Broadcast Engineering
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    • v.22 no.2
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    • pp.162-172
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    • 2017
  • In this paper, we propose facial expression recognition using CNN (Convolutional Neural Network), one of the deep learning technologies. To overcome the disadvantages of existing facial expression databases, various databases are used. In the proposed technique, we construct six facial expression data sets such as 'expressionless', 'happiness', 'sadness', 'angry', 'surprise', and 'disgust'. Pre-processing and data augmentation techniques are also applied to improve efficient learning and classification performance. In the existing CNN structure, the optimal CNN structure that best expresses the features of six facial expressions is found by adjusting the number of feature maps of the convolutional layer and the number of fully-connected layer nodes. Experimental results show that the proposed scheme achieves the highest classification performance of 96.88% while it takes the least time to pass through the CNN structure compared to other models.

The Analysis of User Preference Tendency for Color Temperature Conversion of the Image (영상 색온도 변환에 대한 사용자 선호 경향 분석)

  • Joo, Yong-Soo;Kim, Sang-Kyun
    • Journal of Broadcast Engineering
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    • v.15 no.2
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    • pp.290-303
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    • 2010
  • Recently, researches to improve a quality and a color of a display are being actively studied because of the prosperous growth of the flat panel displays such as LCD, PDP and OLED. Automatically adjusting color temperatures based on user preferences is the one of the researches to provide the optimum display color. In this paper, along with defining the problems of prior methods, the user preferences against the priori defined ranges proposed by the MPEG-7 color temperature descriptor are inspected. Based on the analysis of user preferences, an optimal color temperature conversion curve is proposed. As a result of an analysis by ANOVA, tendencies of the user preferences against each range are proven to be similar to the prior research results. The repetition of the color temperature conversion against an image is not statistically significant.

CLO (Cross Layer Optimization) Technique for Multi-view Video Streaming Service over WiBro Network (WiBro망에서의 다시점 비디오 스트리밍 서비스를 위한 계층 간 최적화 방식)

  • Son, Jung-Hyun;Cho, Ye-Jin;Suh, Doug-Young;Park, Gwang-Hoon;Kim, Kyu-Heon
    • Journal of Broadcast Engineering
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    • v.13 no.5
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    • pp.719-731
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    • 2008
  • This paper defines QoE (Quality of Experience) for multi-view video streaming service over WiBro and proposes the CLO (Cross-Layer Optimization) algorithm can maximize this. Proposal CLO algorithm contains from physical layer to video layer. Under the time-varying wireless channel condition, the CLO technique takes view-wise and the temporal priority of the multi-view video into consideration in order to decide the transmission of frames and its FEC level. At the handover situation, it is shown through computer simulation that the optimal quality of the multi-view video can be achieved using the minimum amount of resources if the proposed CLO technique is applied.

A Fast and Low-complexity Motion Estimation for UHD HEVC (초고화질 영상처리를 위한 HEVC 표준에 적합한 고속 및 저복잡도 움직임 예측기에 대한 연구)

  • Kim, Sungoh;Park, Chansik;Chun, Hyungju;Kim, Jaemoon
    • Journal of Broadcast Engineering
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    • v.18 no.6
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    • pp.808-815
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    • 2013
  • In this paper, we propose a novel fast and low-complexity Motion Estimation (ME) algorithm for Ultra High Definition (UHD) High Efficiency Video Coding (HEVC). Motion estimation occupies 77~81% of the amount of computation in HEVC. After all, the main key of video codec implementation is to find a fast and low-complexity motion estimation algorithm and architecture. We analyze the previous motion estimation algorithms and propose three optimal algorithm to reduce the computation proportion for HEVC. The proposed algorithm uses only 0.36% of the amount of operations compared to full search algorithm while maintaining compression performance with slight loss of 1.1%.