• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.1-8
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• 2006

This paper presents a fast full search algorithm for motion estimation applicable to multiple reference images. The proposed method is an extended version of the rate constrained successive elimination algorithm (RSEA) for multiple reference frame applications. We will show that motion estimation for the reference images temporally preceding the first reference image can be less intensive in computation compared with that for the first reference image. for computational reduction, we will drive a new condition to lead the smaller number of candidate blocks for the best matched block. Simulation results explain that our method reduces computation complexity although it has the same quality as RSEA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1323-1329
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• 2004

This paper presents an enhanced MSEA(multi-level successive elimination algorithm) which is a fast algorithm of the full-search motion estimation. We predict the SAD at the final level using the values of norms at the preceding levels in MSEA and then decide on whether the processing at the following levels should be proceeded or not. We skip the computation at the following levels where the processing is not meaningful anymore. Consequently, we take computational gain. For the purpose of predicting the values of SAD at each level, we first show the theoretical analysis of the value of norm at each level, which is verified by experiments. Based on the analysis a new motion estimation method is proposed and its performance is evaluated.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.55-65
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• 2006

Most of fast block motion estimation algorithms reported so far in literatures aim to reduce the computation in terms of the number of search points, thus do not fit well with multimedia processors due to their irregular data flow. For multimedia processors, proper reuse of data is more important than reducing number of absolute difference operations because the execution cycle performance strongly depends on the number of off-chip memory access. Therefore, in this paper, we propose a Hexagon-shape line search (HEXSLS) algorithm using line search pattern which can increase data reuse from on-chip local buffer, and check sub-sampling points in line search pattern to reduce unnecessary SAD operation. Our experimental results show that the prediction error (MAE) performance of the proposed HEXSLS is similar to that of the full search block matching algorithm (FSBMA), while compared with the hexagon-based search (HEXBS), the HEXSLS outperforms. Also the proposed HEXSLS requires much lesser off-chip memory access than the conventional fast motion estimation algorithm such as the hexagon-based search (HEXBS) and the predictive line search (PLS). As a result, the proposed HEXSLS algorithm requires smaller number of execution cycles on media processor.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.987-992
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• 2004

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the improved diamond search pattern using an motion vector prediction candidate search point by the predicted motion information from the same block of the previous frame. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improves as high as high as 14~24% in terms of average number of search point per motion vector estimation and improved about 0.02~0.37dB on an average except the full search(FS) algorithm.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1434-1437
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• 1987

We present a very simple algorithm for reducing the encoding (codebook search) complexity of vector quantization (VQ), exploiting some features of a vector currently being encoded. A proposed VQ of 16 (=$4{\times}4$) vector dimension and 256 codewords shows a slight performance degradation of about 0.1-0.9 dB, however, with only 16 or 32 among 256 codeword searches, i.e., with just 1/16 or 1/8 search complexity compared to a full-search VQ. And the proposed VQ scheme is also compared to and shown to be a bit superior to tree-search VQ with regard to their SNR performance and memory requirement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1401-1410
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• 1999

In this paper, we propose a fast block matching algorithm using the lower and upper bound of mean absolute difference (MAD) which is calculated at the search region overlapped with neighbor blocks. At first, we calculate the lower bound of MAD and reduce the search point by using this lower bound. In this method, we can get good prediction error performance close to full search block matching algorithm (FSBMA), but there exists some computational complexity that has to be reduced. Therefore, we further reduce the computational complexity by using pixel subsampling besides the lower and upper bound of MAD. Experimental results show that we can remarkably reduce the computational complexity with good prediction error performance close to FSBMA.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.808-815
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• 2013

In this paper, we propose a novel fast and low-complexity Motion Estimation (ME) algorithm for Ultra High Definition (UHD) High Efficiency Video Coding (HEVC). Motion estimation occupies 77~81% of the amount of computation in HEVC. After all, the main key of video codec implementation is to find a fast and low-complexity motion estimation algorithm and architecture. We analyze the previous motion estimation algorithms and propose three optimal algorithm to reduce the computation proportion for HEVC. The proposed algorithm uses only 0.36% of the amount of operations compared to full search algorithm while maintaining compression performance with slight loss of 1.1%.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.84-90
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• 2019

Tremendous computation of full search or lossless motion estimation algorithms for video coding has led development of many fast motion estimation algorithms. We still need proper control of computation and prediction quality. In the paper, we suggest an algorithm that reduces computation effectively and controls computational amount and prediction quality, while keeping prediction quality as almost the same as that of the full search. The proposed algorithm uses multiple thresholds for partial block sum and times of counting unchanged minimum position for each step. It also calculates the partial block matching error, removes impossible candidates early, implements fast motion estimation by comparing times of keeping the position of minimum error for each step, and controls prediction quality and computation easily by adjusting the thresholds. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.78-84
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• 2009

In general video coding systems, motion estimation (ME) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. Fractional pixel motion estimation can improve the video compression rate at the cost of higher computational complexity. It is based on the experimental results that the sum of absolute differences (SAD) shows parabolic shape and thus can be approximated by using interpolation technique. In this paper, we propose a fast fractional pixel search algorithm by combining SASR (Simplified Adaptive Search Range) and the CBCDS (Center Biased Cross-Diamond Search) pattern with the predicted motion vector. Compare with the fractional pel full search and the CBFPS, the proposed CBCDS algorithms can reduce fractional pel search points up to 81.4%, respectively with the PSNR lost about 0.05dB.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.85-91
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• 2013

This paper proposes the data reusable search scan methods for full search and fast search to implement low power Motion Estimation (ME). The proposed Optimized Sub-region Partitioning (OSP) method which divide search region into several sub-region can reduce the number of the required Reconfigurable Register Array (RRA) by half compared to the existing smart snake scan method for the same data reusability. In addition, the proposed Center Biased Search Scan method (CBSS) for various fast search algorithms can improve the data reusability. The performance comparisons show that the proposed search scan methods can reduce the average redundant data loading about 26.9% and 16.1% compared with the existing rater scan and snake scan methods, respectively. Due to the reduction of memory accesses, the proposed search scan methods are quite suitable for low power and high performance ME implementation.