• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.149-157
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• 2015

The 3D-AVC standard aims at improving coding efficiency by applying new techniques for utilizing intra, inter and view predictions. 3D video scenes are rendered with existing texture video and additional depth map. The depth map comes at the expense of increased computational complexity of the encoding process. For real-time applications, reducing the complexity of 3D-AVC is very important. In this paper, we present a fast intra mode decision algorithm to reduce the complexity burden in the 3D video system. The proposed algorithm uses similarity between texture video and depth map. The best intra prediction mode of the depth map is similar to that of the corresponding texture video. The early decision algorithm can be made on the intra prediction of depth map coding by using the coded intra mode of texture video. Adaptive threshold for early termination is also proposed. Experimental results show that the proposed algorithm saves the encoding time on average 29.7% without any significant loss in terms of the bit rate or PSNR value.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.501-506
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• 2009

In the H.264/ AVC video coding standard, the intra-prediction coding with various block sizes offers a considerably high improvement in coding efficiency compared to previous standards. In order to achieve this, H.264/AVC uses the Rate-distortion optimization (RDO) technique to select the best intraprediction mode for a macroblock, and it brings about the drastic increase of the computation complexity of H.264 encoder. To reduce the computation complexity and stabilize the coding performance on visual quality, this paper proposed a fast intra-prediction mode decision algorithm using non-parametric thresholds and simplified directional masks. The use of nonparametric thresholds makes the intra-coding performance not be dependent on types of video sequences and simplified directional masks reduces the compuation loads needed by the calculation of local edge information. Experiment results show that the proposed algorithm is able to reduce more than 55% of the whole encoding time with a negligible loss in PSNR and bitrates and provides the stable performance regardless types of video sequences.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1144-1152
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• 2005

Intra prediction coding is one of the many coding-efficiency oriented tools of H.264/AVC, but it requires high computational complexity. Many fast intra coding algorithms have been proposed to reduce the computational complexity of intra prediction. While most of them have been focused on the mode decision methods themselves, we propose a fast algorithm in which new intra modes are substituted for the conventional intra modes so that the number of intra modes can be reduced. The simulation results show that the proposed method could reduce the encoding time of the overall sequence by $49\%$ without any noticeable degradation of the coding efficiency.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.514-521
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• 2016

The High Efficiency Video Coding (HEVC) standard provides superior coding efficiency by utilizing highly flexible block structure and more diverse coding modes. However, rate-distortion optimization (RDO) process for the decision of optimal block size and prediction mode requires excessive computational complexity. To alleviate the computation load, this paper proposes a new moment-based fast CU size decision algorithm for intra coding in HEVC. In the proposed method, moment values are computed in each CU block to estimate the texture complexity of the block from which the decision on an additional CU splitting procedure is performed. Unlike conventional methods which are mostly variance-based approaches, the proposed method incorporates the third-order moments of the CU block in the design of the fast CU size decision algorithm, which enables an elaborate classification of CU types and thus improves the RD-performance of the fast algorithm. Experimental results show that the proposed method saves 32% encoding time with 1.1% increase of BD-rate compared to HM-10.0, and 4.2% decrease of BD-rate compared to the conventional variance-based fast algorithm.

• 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 information and communication convergence engineering
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• v.7 no.2
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• pp.193-198
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• 2009

The H.264/ AVC video coding standard supports the intra prediction with various block sizes for luma component and a 8x8 block size for chroma components. This new feature of H.264/AVC offers a considerably higher improvement in coding efficiency compared to previous compression standards. In order to achieve this, H.264/AVC uses the Rate-distortion optimization (RDO) technique to select the best intra prediction mode for each block size, and it brings about the drastic increase of the computation complexity of H.264 encoder. In this paper, a fast block size decision algorithm is proposed to reduce the computation complexity of the intra prediction in H.264/AVC. The proposed algorithm computes the smoothness based on AC and DC coefficient energy for macroblocks and compares with the nonparametric criteria which is determined by considering information on neighbor blocks already reconstructed, so that deciding the best probable block size for the intra prediction. Also, the use of non-parametric criteria makes the performance of intra-coding not be dependent on types of video sequences. The experimental results show that the proposed algorithm is able to reduce up to 30% of the whole encoding time with a negligible loss in PSNR and bitrates and provides the stable performance regardless types of video sequences.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.388-392
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• 2014

This paper proposes an early termination method of a block vector search for fast encoding of high efficiency video coding (HEVC) screen content coding (SCC). In the proposed algorithm, two blocks indicated by two block vector predictors (BVPs) were first employed as an intra block copy (IBC) search. If the sum of absolute difference (SAD) value of the block is less than a threshold defined empirically, an IBC BV search is terminated early. The initial threshold for early termination is derived by statistical analysis and it can be modified adaptively based on a quantization parameter (QP). The proposed algorithm is evaluated on SCM-2.0 under all intra (AI) coding configurations. Experimental results show that the proposed algorithm reduces IBC BV search time by 29.23% on average while the average BD-rate loss is 0.41% under the HEVC SCC common test conditions (CTC).

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.20-27
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• 2009

H.264/AVC video coding standard adapting a rate-distortion optimization technique to select the best coding mode with multi reference frames for each macroblock gets a higher coding efficiency than those of previous video coding standards but the computational complexity increases drastically. Therefore, many fast mode decision algorithms are proposed to reduce the computational complexity. Among them, we propose a fast intra mode decision algorithm based on directional information of I4MB. The proposed algorithm achieves consistent time saving about 15% in IPPP sequences and 44% in all I frame sequences with negligible loss in PSNR and small increment of bit rate compared with that of JM11.0.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.790-800
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• 2009

For the improvement of coding efficiency, the H.264/AYC standard uses new coding tools such as 1/4-pel-accurate motion estimation, multiple references, intra prediction, loop filter, variable block size etc. Using these coding tools, H.264/AYC has achieved significant improvements from rate-distortion point of view compared to existing standards. However, the encoder complexity was greatly increased due to these coding tools. We focus on the complexity reduction method of intra macroblock mode selection. The proposed algorithm for fast intra mode selection calculates the edge activity in transform domain, and performs fast encoding of intra frame in H.264/AYC through the fast prediction mode selection of intra4x4 and chrominance blocks. Simulation results show that the proposed method saves about 59.76% for QCIF sequences and 65.03% for CIF sequences of total encoding time, while bitrate increase and PSNR decrease are very small.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.