• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.859-869
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• 2012

The Multi-view Video Coding (MVC) which is exploiting disparities between views has been developed to improve the coding efficiency of multi-view video. But MVC has a problem of having high computing complexities because of disparity estimation. This paper propose a fast mode decision for non-anchor picture to reduce the computational time of MVC. The proposed method uses two phases. Anchor pictures in hierarchical B picture structure have a higher correlation with prediction mode selection of non-anchor pictures, so in the first phase, prediction mode of non-anchor pictures is selected by exploiting the macro-block regions in anchor picture. In the second phase, we select a reference direction of inter prediction mode exploiting a higher correlation among reference directions of inter prediction modes of 7 block sizes. Experimental results show that the proposed method could save average about 44% in the encoding time with negligible coding efficiency losses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6C
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• pp.579-584
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• 2007

Recently various prediction structures have been proposed to exploit inter-view correlation among multi-view video sequences. In this paper, we propose a QP(quantization parameter) selection method for the B frame inserted in the first frames of each GOP(group of pictures), where we change QP for the B frame adaptively to achieve uniform picture quality and overall coding gain. Each B frame is coded with reference to two frames in its adjacent views. We calculate QP for the B frame based on the correlation between the two reference frames, calculated using their rate-distortion costs. By applying the proposed method to the MVC reference prediction structure, we have improved the coding gain by 0.09$\sim$0.16 dB.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.83-93
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• 2012

This paper proposes a method to efficiently encode multi-view color videos and depth maps. The proposed coding method for multi-view color videos and depth maps can improve the coding efficiency by additional inter-view prediction, as well as inter-frame prediction. By means of the proposed method, we achieved the coding gain of approximately 55% for 2-view color videos and approximately 12% for 2-view depth maps. For 3-view case, we found that the proposed system yields 54% of coding gain from outer view color videos and 56% of coding gain from center view color videos, respectively. Moreover, for 3-view depth map case, approximately 11% of coding gain from outer view and 13% of coding gain from center view are obtained with the proposed coder, respectively.

• 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.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.328-338
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• 2008

Multi-view video coding (MVC) based on H.264/AVC encodes multiple views efficiently by using a prediction scheme that exploits inter-view correlation among multiple views. However, with the increase of the number of views and use of inter-view prediction among views, total encoding time will be increased in multiview video coding. In this paper, we propose a fast mode decision using both MB(Macroblock)-based region segmentation information corresponding to each view in multiple views and global disparity vector among views in order to reduce encoding time. The proposed method achieves on average 40% reduction of total encoding time with the objective video quality degradation of about 0.04 dB peak signal-to-noise ratio (PSNR) by using joint multi-view video model (JMVM) 4.0 that is the reference software of the multiview video coding standard.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.9-18
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• 2014

Recently, many researches have been focused on multi-view video applications and services such as wireless video surveillance networks, wireless video sensor networks and wireless mobile video. In multi-view video signal processing, to exploit the strong correlation between images acquired by different cameras plays great role in developing a core technique of multi-view video coding. This paper proposes an adaptive multi-view video interpolation technique which is applicable for multi-view distributed video coding without requiring any cooperation amongst the cameras. The proposed algorithm estimates the non-linear moving blocks and employs disparity compensated view prediction, and then fills in the unreliable blocks. Through computer simulations, it is shown that the proposed method outperforms the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.721-726
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• 2011

The compression performance of HEVC (high efficiency video coding) is improved 40%, compared to H.264/AVC. Since the existing 3D video CODEC is based on H.264/AVC or MPEG-2, we can improve the compression performance when we use the proposed stereoscopic video coding method based on HEVC. Since the stereoscopic video has the temporal and inter-view correlations, the videos of the left and right cameras encode together to improve the performance. Especially, we implemented the proposed technique using HM(HEVC test model) 3.4. To compare the performance of the proposed method, we only compare the right view video which is coded using the inter-view prediction. The proposed method which is considered inter-view correlation is improved the performance which BDBR reduce about 36.24% and BDPSNR increase approximately 1.19 dB compared to the separated-coding method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1730-1747
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• 2018

Multi-view video plus depth (MVD) is a mainstream format of 3D scene representation in free viewpoint video systems. The advanced 3D extension of the high efficiency video coding (3D-HEVC) standard introduces new prediction tools to improve the coding performance of depth video. However, the depth video in 3D-HEVC is time consuming. To reduce the complexity of the depth video inter coding, we propose a fast coding unit (CU) size and mode decision algorithm. First, an off-line trained Bayesian model is built which the feature vector contains the depth levels of the corresponding spatial, temporal, and inter-component (texture-depth) neighboring largest CUs (LCUs). Then, the model is used to predict the depth level of the current LCU, and terminate the CU recursive splitting process. Finally, the CU mode search process is early terminated by making use of the mode correlation of spatial, inter-component (texture-depth), and inter-view neighboring CUs. Compared to the 3D-HEVC reference software HTM-10.0, the proposed algorithm reduces the encoding time of depth video and the total encoding time by 65.03% and 41.04% on average, respectively, with negligible quality degradation of the synthesized virtual view.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.245-246
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• 2008

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.405-408
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• 2017

Based on the fact that high similarities exist between viewpoints of multi-view images, MV-HEVC achieves high encoding efficiency by performing conventional temporal direction prediction in a single viewpoint as well as inter-view prediction between viewpoints. In this paper, we propose to integrate SHVC and MVC (Multi-view Video Coding) to implement scalable multi-view video encoder using HEVC as a base layer. According to experimental results, it is verified that the BD-PSNR improvement reaches up to 1.5dB while reducing the BD-Bitrate by around 50~60%.