• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.836-846
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• 2014

To expedite UHD (Ultra High Definition) video service, the HEVC (High-Efficiency Video Coding) technology has recently been standardized and it achieves two times higher compression efficiency than the conventional H.264/AVC. To obtain the improved efficiency, however, it employs many complex methods which need complicated calculation, thereby resulting in a significantly increased computational complexity when compared to that of H.264/AVC. For example, to improve the coding efficiency of intra frame coding, up to 35 intra prediction modes are defined in HEVC, but this results in an increased encoding time than the H.264/AVC. In this paper, we propose a fast intra prediction mode decision scheme which reduces computational complexity by changing the number of intra prediction mode in accordance with the percentage of PU sizes for a given video resolution, and by classifying the 35 intra prediction modes into 4 categories considering video resolution and quantization parameter. The experimental results show that the total encoding time is reduced by about 7% on average at the cost of only 2% increase in BD-rate.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.11
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• pp.41-47
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• 2016

High efficiency video coding (HEVC) employs a coding tree unit (CTU) to improve the coding efficiency. A CTU consists of coding units (CU), prediction units (PU), and transform units (TU). All possible block partitions should be performed on each depth level to obtain the best combination of CUs, PUs, and TUs. To reduce the complexity of block partitioning process, this paper proposes the PU mode skip algorithm with region of interest (RoI) selection using motion vector. In addition, this paper presents the CU depth level skip algorithm using the co-located block information in the previously encoded frames. First, the RoI selection algorithm distinguishes between dynamic CTUs and static CTUs and then, asymmetric motion partitioning (AMP) blocks are skipped in the static CTUs. Second, the depth level skip algorithm predicts the most probable target depth level from average depth in one CTU. The experimental results show that the proposed fast CU decision algorithm can reduce the total encoding time up to 44.8% compared to the HEVC test model (HM) 14.0 reference software encoder. Moreover, the proposed algorithm shows only 2.5% Bjontegaard delta bit rate (BDBR) loss.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.132-141
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• 2019

The necessity of transmitting video data over a narrow-bandwidth exists steadily despite that video service over broadband is common. In this paper, we propose a scalable video coding framework for low-resolution video transmission over a very narrow-bandwidth network by super-resolution of decoded frames of a base layer using a convolutional neural network based super resolution technique to improve the coding efficiency by using it as a prediction for the enhancement layer. In contrast to the conventional scalable high efficiency video coding (SHVC) standard, in which upscaling is performed with a fixed filter, we propose a scalable video coding framework that replaces the existing fixed up-scaling filter by using the trained convolutional neural network for super-resolution. For this, we proposed a neural network structure with skip connection and residual learning technique and trained it according to the application scenario of the video coding framework. For the application scenario where a video whose resolution is $352{\times}288$ and frame rate is 8fps is encoded at 110kbps, the quality of the proposed scalable video coding framework is higher than that of the SHVC framework.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.544-554
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• 2012

Screen content refers to images or videos generated by various electronic devices such as computers or mobile phones, whereas natural content refers to images captured by cameras. Screen contents show different statistical characteristics from natural images, so the conventional video codecs which were developed mainly for the coding of natural videos cannot guarantee good coding performances for screen contents. Recently, researches on efficient SCC(Screen Content Coding) are being actively studied, and especially at ongoing JCT-VC(Joint Collaborative Team on Video Coding) meeting for HEVC(High Efficiency Video Coding) standard, SCC issues are being discussed steadily. In this paper, we analyze the performances of high efficient coding tools in HM(HEVC Test Model) on SCC, and present an optimized SCC model based on the analysis results. We also present the characteristics of screen contents and the future research issues as well.

• ETRI Journal
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• v.38 no.1
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• pp.185-194
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• 2016

In this paper, a novel rate control scheme for low delay video coding of High Efficiency Video Coding (HEVC) is proposed. The proposed scheme is developed by considering a new temporal prediction structure of HEVC. In the proposed scheme, the relationship between bit rate and quantization step is exploited firstly to formulate an accurate quadratic rate-quantization (R-Q) model. Secondly, a method of determining the quantization parameters (QPs) for the first frames within a group of pictures is proposed. Thirdly, an accurate frame-level bit allocation method is proposed for HEVC. Finally, based on the proposed R-Q model and the target bit allocated for the frame, the QPs are predicted for coding tree units by using rate-distortion (R-D) optimization. We compare our scheme against that of three other state-of-the-art rate control schemes. Experimental results show that the proposed rate control scheme can increase the Bjøntegaard delta peak signal-to-noise ratio by 0.65 dB and 0.09 dB on average compared with the JCTVC-I0094 and JCTVC-M0036 schemes, respectively, both of which have been implemented in an HEVC test model encoder; furthermore, the proposed scheme achieves a similar R-D performance to Wang's scheme, as well as obtaining the smallest bit rate mismatch error of all the schemes.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.734-741
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• 2012

A new lossless intra coding method based on residual transform is applied to the next generation video coding standard HEVC (High Efficiency Video Coding). HEVC includes a multi-directional spatial prediction method to reduce spatial redundancy by using neighboring samples as a prediction for the samples in a block of data to be encoded. In the new lossless intra coding method, the spatial prediction is performed as samplewise DPCM (Difference Pulse Code Modulation) but is implemented as block-based manner by using residual transform and secondary residual transform on the HEVC standard. Experimental results show that the new lossless intra coding method reduces the bit rate by approximately 6.45% in comparison with the lossless intra coding method previously included in the HEVC standard.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.180-181
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• 2013

High efficiency video coding (HEVC) appears due to the demand on high compression video coding beyond H.264/AVC in ultra-high definition (UHD) videos. As for intra prediction, HEVC has 35 prediction modes while H.264/AVC has 9 intra modes. To exploit the spatial correlation, we adopt an edge detection method, establish the edge map, and adaptively select the candidate modes using the acquired edge information in a block. The number of the candidate modes is determined through trade-off between computational complexity and coding efficiency. Besides, the range of coding unit sizes is determined using the uniqueness of the edge directions for the given image block. As a result, we reduced the encoding time by 56.8% at the cost of 2.5% BD-BR increase on average compared to Full modes at the HEVC reference software (HM 6.0 [1]).

• ETRI Journal
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• v.34 no.5
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• pp.753-758
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• 2012

As the next-generation video coding standard, High Efficiency Video Coding (HEVC) has adopted advanced coding tools despite the increase in computational complexity. In this paper, we propose a selective bi-prediction method to reduce the encoding complexity of HEVC. The proposed method evaluates the statistical property of the sum of absolute differences in the motion estimation process and determines whether bi-prediction is performed. A performance comparison of the complexity reduction is provided to show the effectiveness of the proposed method compared to the HEVC test model version 4.0. On average, 50% of the bi-prediction time can be reduced by the proposed method, while maintaining a negligible bit increment and a minimal loss of image quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.778-786
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• 2008

The H.264/AVC video coding standard shows superior coding efficiency by adopting many new techniques. However, the encoding complexity increases greatly to achieve higher coding efficiency. Especially, the rate distortion optimization technique, which is used to decide the intra-prediction mode, increases the encoding complexity. In this paper, we propose an efficient intra-prediction mode decision method. By using the variance of pixel values and the edge direction, the computational complexity of the intra-prediction mode decision is greatly reduced.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.492-499
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• 2019

HEVC is the high efficiency video coding standard, which provides better coding efficiency contrasted with the other video coding standard. But at the same time the computational complexity increases drastically. Thirty-five kinds of intra-prediction modes are defined in HEVC, while 9 kinds of intra prediction modes are defined in H.264/AVC. This paper proposes a fast rough mode decision (RMD) algorithm which adopts the smoothness of the up-reference pixels and the left-reference pixels to decrease the computational complexity. The three step search method is implemented in RMD process. The experimental results compared with HM13.0 indicate that the proposed algorithm can save 39.7% of the encoding time, while Bjontegaard delta bitrate (BDBR) is increased slightly by 1.35% and Bjontegaard delta peak signal-to-noise ratio (BDPSNR) loss is negligible.