• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.86-96
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• 2002

In video conferencing system using H.263 encoding and decoding time is as important as compression rate is. To reduce encoding time, a number of methods were proposed. We use a method of them that reduces the computational complexity in motion estimation. The complexity is determined by three factors, such as a cost function, a search range parameter, and a motion search algorithm. In fact, it takes a lot of time to encode the video data on account of the cost function factor. That's the reason that we use the factor to reduce encoding time. In this paper, we tried to reduce total encoding time by reducing the number of calling the cost function. In case of a little moving, our algorithm enabled faster motion searching than TSS(Three Step Search) and NTSS(New TSS). Here, we called the algorithm by an ITSS(Improved TSS) that improves a shortcoming of NTSS requiring more checkpoints than TSS. For an experimentation, our algorithm was compared to other algorithms using PSNR, file size and SAD call times.

• 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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.125-128
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• 2000

The conventional fractal decoding was required a vast amount computational complexity. Since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested to that each range block was classified to iterated and non-iterated regions. If IFS region is contractive, then it can be performed a fast decoding. In this paper, a searched region of the domain in the encoding is limited to the range region that is similar with the domain block, and IFS region is a minimum. So, it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.264-266
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• 2016

During the $2^{nd}$ JVET (Joint Group on Future Video Coding Technology Exploration) meeting, up to 22 coding tools focusing on Future Video Coding (FVC) were proposed. Despite that the application of proposed coding tools has a considerable performance enhancement, however, the encoding time of Joint Exploration Model (JEM) software is over 20 times for All Intra coding mode, 6 times for Random Access coding mode, of HEVC reference model (HM), and decoding time is 1.6 times for All Intra coding mode, 7.9 times for Random Access coding mode, of HM. This paper focuses on analyzing the complexity of the JEM software compared with HM.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.142-147
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• 2018

We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.

• 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.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.547-562
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• 2011

We establish a new formalism of the non-periodic autocorrelation function (NPAF) of two sequences, which is suitable for the computation of the NPAF of any two sequences. It is shown, that this encoding of NPAF is efficient for sequences of small weight. In particular, the check for two sequences of length n having weight w to have zero NPAF can be decided in $O(n+w^2{\log}w)$. For n > w^2{\log}w$, the complexity is O(n) thus we cannot expect asymptotically faster algorithms.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.117-123
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• 2017

N-continuous orthogonal frequency division multiplexing (OFDM) is a precoding method for sidelobe suppression of OFDM signals and seamlessly connects OFDM symbols up to the high-order derivative for sidelobe suppression, which is suitable for suppressing out-of-band radiation. However, it severely degrades the error rate as it increases the continuous derivative order. Two schemes for orthogonal precoding of N-continuous OFDM have been proposed to achieve an ideal error rate while maintaining sidelobe suppression performance; however, the large size of the precoder matrices in both schemes causes very high computational complexity for precoding and decoding. This paper proposes matrix decomposition of precoder matrices with a large size in the orthogonal precoding schemes in order to reduce computational complexity. Numerical experiments show that the proposed method can drastically reduce computational complexity without any performance degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.632-638
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• 2010

In this paper, we propose a fixed-complexity sphere encoder (FSE) for multi-user MIMO (MU-MIMO) systems. The Proposed FSE accomplishes a scalable tradeoff between performance and complexity. Also, because it has a parallel tree-search structure, the proposed encoder can be easily pipelined, leading to a tremendous reduction in the precoding latency. The complexity of the proposed encoder is also analyzed, and we propose two techniques that reduce it. Simulation and analytical results demonstrate that in a $4\times4$ MU-MIMO system, the complexity of the proposed FSE is 16% that of the conventional QRD-M encoder (QRDM-E). Also, the encoding throughput of the proposed endoder is 7.5 times that of the QRDM-E with tolerable degradation in the BER performance, while achieving the optimum diversity order.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.408-427
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• 2011

Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter $16{\times}16$ modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.