• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1825-1839
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• 2015

The final draft of the latest video coding standard, High Efficiency Video Coding (HEVC), was approved in January 2013. The coding efficiency of HEVC surpasses its predecessor, H.264/MPEG-4 Advanced Video Coding (AVC), by using only half of the bitrate to encode the same sequence with similar quality. However, the complexity of HEVC is sharply increased compared to H.264/AVC. In this paper, a method is proposed to decrease the complexity of intra coding in HEVC. Early pruning and an early splitting strategy are applied to the quadtree structure of coding tree units (CTU) and residual quadtree (RQT). According to our experiment, when our method is applied to sequences from Class A to Class E, the coding time is decreased by 44% at the cost of a 1.08% Bjontegaard delta rate (BD-rate) increase on average.

• ETRI Journal
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• v.35 no.2
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• pp.270-280
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• 2013

A fast intra-prediction method is proposed for High Efficiency Video Coding (HEVC) using a fast intra-mode decision and fast coding unit (CU) size decision. HEVC supports very sophisticated intra modes and a recursive quadtree-based CU structure. To provide a high coding efficiency, the mode and CU size are selected in a rate-distortion optimized manner. This causes a high computational complexity in the encoder, and, for practical applications, the complexity should be significantly reduced. In this paper, among the many predefined modes, the intra-prediction mode is chosen without rate-distortion optimization processes, instead using the difference between the minimum and second minimum of the rate-distortion cost estimation based on the Hadamard transform. The experiment results show that the proposed method achieves a 49.04% reduction in the intra-prediction time and a 32.74% reduction in the total encoding time with a nearly similar coding performance to that of HEVC test model 2.1.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.157-162
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• 2012

In this paper, we propose a new intra mode coding method using the candidate mode table. In the conventional HEVC, if the predicted most probable mode (MPM) is not same with the current prediction mode, the current prediction mode is encoded using the fixed length code (FLC). However, since a large number of modes are used in HEVC, the codeword length of FLC gets longer. In this paper, we generate the candidate mode table from neighboring blocks and encode the obtained intra mode index using Golomb-Rice code instead of FLC, when the predicted MPM is not identical to the current mode. From the experiment, we verified that the proposed method reduces the BD-rate by 0.5% on average, compared to the HEVC intra mode coding method.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.495-502
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• 2018

JVET (Joint Video Exploration Team) which explored evolving technologies of video coding with capabilities beyond HEVC (High Efficiency Video Coding), released a references software codec named the Joint Exploration Model (JEM) for performance verification of coding technologies. JEM has 67 intra prediction modes that extend the 35 modes of HEVC for intra prediction. Therefore, the enhancement of the coding performance is limited due to the overhead of prediction mode coding. In this paper, we analyze the probabilities of prediction modes selections, and then we propose a more efficient intra prediction mode coding based on the results of analyzed mode occurrence. In addition, we propose a context modeling for CABAC (Context-Adaptive Binary Arithmetic Coding) of the proposed mode coding. Experimental results show that the BD-rate gain is 0.02% on the AI (All Intra) coding structure compared to JEM 7.0. We need to optimize context modeling for additional coding performance enhancement.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.332-340
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• 2022

Recently, with the development of deep learning and artificial neural network technologies, research on the application of neural network has been actively conducted in the field of video coding. In particular, deep learning-based intra prediction is being studied as a way to overcome the performance limitations of the existing intra prediction techniques. This paper presents a method of context-adaptive neural network-based intra prediction model training and its coding performance analysis. In other words, in this paper, we implement and train a known intra prediction model based on convolutional neural network (CNN) that predicts a current block using contextual information from reference blocks. Then, we integrate the trained model into HM16.19 as an additional intra prediction mode and evaluate the coding performance of the trained model. Experimental results show that the trained model gives 0.28% BD-rate bit saving over HEVC in All Intra (AI) coding mode. In addition, the coding performance change of training considering block partition is also presented.

• 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]).

• 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.

• Journal of Multimedia Information System
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• v.4 no.2
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• pp.73-78
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• 2017

The Future Video Coding (FVC) is a new state of the art video compression standard that is going to standardize, as the next generation of High Efficiency Video Coding (HEVC) standard. The FVC standard applies newly designed block structure, which is called quadtree plus binary tree (QTBT) to improve the coding efficiency. Also, intra and inter prediction parts were changed to improve the coding performance when comparing to the previous coding standard such as HEVC and H.264/AVC. Experimental results shows that we are able to achieve the average BD-rate reduction of 25.46%, 38.00% and 35.78% for Y, U and V, respectively. In terms of complexity, the FVC takes about 14 times longer than the consumed time of HEVC encoder.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.180-181
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• 2019

This paper proposes a rate control algorithm for intra coding frame in HEVC encoder using a deep learning approach. The proposed algorithm is designed for CTU level bit allocation in intra frame by considering visual features spatially and temporally. Our features are generated using visual geometry group (VGG-16) with deep convolutional layers, then it is used for bit allocation per each CTU within an intra frame. According to our experiments, the proposed algorithm can achieve -2.04% Luma component BD-rate gain with minimal bit accuracy loss against the HM-16.20 rate control model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.767-773
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• 2017

In this paper, we propose a design of Intra prediction angular mode decision for HEVC encoder. Intra prediction coding of HEVC is a method for predicting a current block by referring to samples reconstructed around a current block. Intra prediction supports a total of 35 modes with 1 DC mode, 1 Planar mode, and 33 Angular modes. Intra prediction coding of HEVC works by performing all 35 modes for efficient encoding. However, in order to process all of the 35 modes, the computational complexity and operational time required are high. Therefore, this paper proposes comparing the difference in the value of the original pixel, using an algorithm that determines angular mode efficiently. This new algorithm reduces the Hardware size. The hardware which is proposed was designed using Verilog HDL and was implemented in 65nm technology. Its gate count is 14.9K and operating speed is 2GHz.