• Journal of Communications and Networks
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• v.12 no.1
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• pp.5-10
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• 2010

This paper introduces a new fast motion estimation based on estimating a block matching error (i.e., sum of absolute difference (SAD)) between blocks which can eliminate an impossible candidate block much earlier than a conventional partial distortion elimination (PDE) scheme. The basic idea of the proposed scheme is based on predicting the total SAD of a candidate block using its partial SAD. In particular, in order to improve prediction accuracy and computational efficiency, a sub-sample based block matching and a selective pixel-based approaches are employed. In order to evaluate the proposed scheme, several baseline approaches are described and compared. The experimental results show that the proposed algorithm can reduce the computations by about 44% for motion estimation at the cost of 0.0005 dB quality degradation versus the general PDE algorithm.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1439-1445
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• 2007

In this paper, we propose a fast motion estimation algorithm using initial matching errors by sorting square sub-blocks to find complex sub-block area adaptively based on partial calculation of SAD(sum of absolute difference) while keeping the same prediction quality compared with the PDE(partial distortion elimination) algorithm. We reduced unnecessary calculations with square sub-block adaptive matching scan based initial SAD calculation of square sub-block in each matching block. Our algorithm reduces about 45% of computations for block matching error compared with conventional PDE(partial distortion elimination) algorithm without any degradation of prediction quality, and for algorithm will be useful to real-time video coding applications using MPEG-4 AVC or MPEG-2.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1531-1536
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• 2016

In this paper, we propose a fast motion estimation algorithm which is important in performance of video encoding. Even though so many fast algorithms for motion estimation have been published due to its tremendous computational amount of for full search algorithm, efforts for reducing computations in motion estimation still remain. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality the same as that of the full search. The proposed algorithm does not calculate block matching error for each candidate at once to find motion vectors but divides the calculation procedure into several steps and calculates partial sum of block errors. By doing that, we can estimate the minimum error point early and get the enhancement of calculation speed by reducing unnecessary computations. The proposed algorithm uses smaller computations than conventional fast search algorithms with the same prediction quality as full search.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.62-67
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• 2017

In this paper, we propose a fast motion estimation algorithm which is important in performance of video encoding. Even though so many fast algorithms for motion estimation have been published due to tremendous computational amount of full search algorithm, efforts for reducing computations of motion estimation still remain. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality the same as that of the full search. The proposed algorithm does not calculate block matching error for each candidate directly to find motion vectors but divides the calculation procedure into several steps and calculates partial sum of block errors for candidates with high priority. By doing that, we can find the minimum error point early and get the enhancement of calculation speed by reducing unnecessary computations. The proposed algorithm uses smaller computations than conventional fast search algorithms with the same prediction quality as the full search algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.199-205
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• 2018

So many fast motion estimation algorithms for prediction quality and computational reduction have been published due to tremendous computations of full search algorithm. In the paper, we suggest an algorithm that reduces computation effectively, while keeping prediction quality as almost same as that of the full search. The proposed algorithm based on multiple threshold filter calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, removes impossible candidates, and calculates optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain the better performance of calculation speed by reducing unnecessary computations. 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 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 Broadcast Engineering
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• v.23 no.5
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• pp.628-635
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• 2018

In this paper, we propose a fast motion estimation algorithm which is important in video encoding. So many fast motion estimation algorithms have been published for improving prediction quality and computational reduction. In the paper, we propose an algorithm that reduces unnecessary computation, while almost keeping prediction quality compared with the full search algorithm. The proposed algorithm calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, and finds optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain fast computational speed by reducing unnecessary computations. Additionally, the proposed algorithm can be used with conventional fast motion estimation algorithms and prove it in the experimental results.