• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2376-2385
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• 1994

In receiving the digital TV signal, both decoding delay and the channel hopping delay are very critical factors in applications. The intra-slice coding in the MPEG-2 SIMPLE PROFLE of No B-picture is one of the primary methods for short delay time in video decoding. It has the advantage of short decoding delay, but has the drawback of long channel hopping delay time. In this paper, we propose a method to reduce the channel delay with negligible loss in SNR performance. It is shown that dividing pictures into several regions of slices and adding some restriction in motion vector search for inter-frame coding. hence the random acess points are effectively increased. and the channel hopping delay is reduced.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.12
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• pp.1589-1598
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• 1999

Conventional MSE or PSNR based methods for objective picture quality assessment of moving picture coder are not well correlated with subjective human evaluation. In recent years, the design of better objective quality assessment has attracted much intention and several picture quality metrics based on the properties of Human Visual System has been proposed. This paper proposes new metric which is appropriate for objective picture quality assessment of block based moving picture coder by considering frequency sensitivity, inter-intra channel masking and several distortion artifacts caused by block based coding. The experimental results show that the proposed method is good correlated with subjective assessment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.148-150
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• 2020

최근 VVC(Versatile Video Coding) 표준 완료 이후 JVET(Joint Video Experts Team)은 인공신경망 기반의 비디오 부호화를 위한 AhG(Ad-hoc Group) 구성하고 인공지능을 이용한 비디오 압축 기술들을 검증하고 있으며, MPEG(Moving Picture Experts Group)에서는 DNNVC(Deep Neural Network based Video Coding) 활동을 통해 딥러닝 기반의 차세대 비디오 부호화 표준 기술을 탐색하고 있다. 본 논문은 VVC 에 채택된 신경망 기반의 기술인 MIP(Matrix Weighted Intra Prediction)를 참조하여, MIP 모델의 학습에서 손실함수가 예측 성능에 미치는 영향을 분석한다. 즉, 예측의 왜곡(MSE)만을 고려한 경우와 예측오차의 부호화 비용도 함께 반영한 손실함수를 비교한다. 실험을 위해 HEVC(High Efficiency Video Coding) 화면내 예측 대비 평균적인 PSNR 향상 정도를 나타내는 성능 지표(��PSNR)를 정의한다. 실험결과 예측오차의 부호화 특성을 반영하는 손실함수를 이용한 학습이 MSE 만 고려한 학습 대비 ��PSNR 기준 평균 0.4dB 향상됨을 보였다.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.1-7
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• 2017

Joint Collaborative Team on Video Coding (JCT-VC) of ISO/IEC MPEG and ITU-T developed the HEVC Screen Content Coding (HEVC SCC) standard as the HEVC extension for the screen content video coding. The Intra Block Copy (IBC) is the most effective tool adopted in HEVC SCC and predicts current block from already reconstructed neighboring blocks in the same picture. To reduce the amount of data in BV (Block Vector) to be transmitted, a BV predictor (BVP) is used to generate the BV differences in the IBC BV coding. In this paper, we analyze the current BV prediction process using HEVC reference software SCM-2.0 and SCM-4.0. Based on the analysis results, we propose an improved BVP candidate selection algorithm by adding a search process for adjacent BVs in addition to the existing spatial BVP candidates. Experimental results show that the BD-rate reduction of our proposed improvements ranges from 0.2% to 1%.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1134-1142
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• 2019

Detection of double compression is one of the most efficient ways of remarking the validity of videos. Many methods have been introduced to detect HEVC double compression with different coding parameters. However, HEVC double compression detection under the same coding environments is still a challenging task in video forensic. In this paper, we introduce a novel method based on the frame partitioning information in intra prediction mode for detecting double compression in with the same coding environments. We propose to extract statistical feature and Deep Convolution Neural Network (DCNN) feature from the difference of partitioning picture including Coding Unit (CU) and Transform Unit (TU) information. Finally, a softmax layer is integrated to perform the classification of the videos into single and double compression by combing the statistical and the DCNN features. Experimental results show the effectiveness of the statistical and the DCNN features with an average accuracy of 87.5% for WVGA and 84.1% for HD dataset.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.35-45
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• 2024

In this paper, we propose an intra prediction method for depth picture using CNN and Attention mechanism. The proposed method allows each pixel in a block to predict to select pixels among reference area. Spatial features in the vertical and horizontal directions for reference pixels are extracted from the top and left areas adjacent to the block, respectively, through a CNN layer. The two spatial features are merged into the feature direction and the spatial direction to predict features for the prediction block and reference pixels, respectively. the correlation between the prediction block and the reference pixel is predicted through attention mechanism. The predicted correlations are restored to the pixel domain through CNN layers to predict the pixels in the block. The average prediction error of intra prediction is reduced by 5.8% when the proposed method is added to VVC intra modes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2020-2025
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• 2006

H.264/AVC is newest video coding standard of the ITU-T Video coding Experts Group and the ISO/IEC Moving Picture Expets Group. Recently H.264/AVC has been adopted as a video compression standard in DMB and multimedia equipments. In this paper, we propose a H.264/AVC intra frame decoder which can minimize the memory usage and chip size. The proposed intra frame decoder is described in VHDL language and simulated in model_sim. It was verified in chip level by downloading to XCV1000E FPGA chip.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.167-169
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• 2005

The occurrence of a single bit error in transmission bitstream leads to serious temporal and spatial errors. Because moving picture coding as MPEG-2 based on block coding algorithm uses variable length coding and motion compensation coding algorithm. In this paper, we propose algorithm to conceal occurred error of I-frames in transmission channel using data of the neighboring blocks in decoder. We divide a damaged macroblock of I-frame into four sub blocks and compose new macroblock using the neighboring blocks for each sub block. We estimate the block with minimum difference value through block matching with previous frame for new macroblocks and replace each estimated block with damaged sub block in the same position. Through simulation results, the proposed algorithm will be applied to a characteristic of moving with effect and shows better performance than conventional error concealment algorithms from visual and PSNR of view.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.35-44
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• 2022

In this paper, we propose an intra-picture prediction method by a quadratic surface modeling method for depth video coding. The pixels of depth video are transformed to 3D coordinates using distance information. A quadratic surface with the smallest error is found by least square method for reference pixels. The reference pixel can be either the upper pixels or the left pixels. In the intra prediction using the quadratic surface, two predcition values are computed for one pixel. Two errors are computed as the square sums of differences between each prediction values and the pixel values of the reference pixels. The pixel sof the block are predicted by the reference pixels and prediction method that they have the lowest error. Comparing with the-state-of-art video coding method, simulation results show that the distortion and the bit rate are improved by up to 5.16% and 5.12%, respectively.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.311-316
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• 2017

High Efficiency Video Coding (HEVC) is the newest video coding standard for improvement in video data compression. This new standard provides a significant improvement in picture quality, especially for high-resolution videos. A quadtree-based structure is created for the encoding and decoding processes and the rate-distortion (RD) cost is calculated for all possible dimensions of coding units in the quadtree. To get the best combination of the block an optimization process is performed in the encoder, called rate distortion optimization (RDO). In this work we are proposing a novel approach to enhance the overall RDO process of HEVC encoder. The proposed algorithm is performed in two steps. In the first step, like HEVC, it performs general rate distortion optimization. The second step is an extra checking where a SSIM based cost is evaluated. Moreover, a fast SSIM (FSSIM) calculation technique is also proposed in this paper.