• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of Broadcast Engineering
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• v.12 no.3
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• pp.278-288
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• 2007

We propose the fast full search algorithm that reduces the computational load of the block matching algorithm which is used for a motion estimation in the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion picture. However we proposed the efficient motion estimation method which is good for the fast and slow motion picture. Firstly, when finding the initial threshold value, we use the expanded predictor that can approximately calculate minimum threshold value. The proposed algorithm estimates the motion in the new search order after partitioning the search window and adapt the directional search order in the re-divided search window. At the result, we can check that the proposed algorithm reduces the computational load 94% in average compared to the conventional spiral full search algorithm without any loss of image quality.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.991-999
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• 2010

In this paper, we propose a fast motion estimation algorithm for video encoding. Conventional fast motion estimation algorithms have a serious problem of low prediction quality in some frames. However, full search based fast algorithms have low computational reduction ratio. In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution probability of motion vectors and adaptive search patterns and block matching criteria. By taking different search patterns and error criteria of block matching according to distribution probability of motion vectors, we can reduces only unnecessary computations efficiently. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.9-15
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• 2007

We propose the fast full search algorithm that reduces the computation of the block matching algorithm which is used for motion estimation of the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion pictures. However the proposed method is good for the fast and slow motion because it estimates the motion in the new search order after partitioning the search window. Also, when finding the motion vector, this paper presents the method that reduces the complexity by computing the matching error in the order which is determined by local image complexity. The proposed algorithm reduces the computation up to 99% for block matching error compared with the conventional spiral full search algorithm without any loss of image quality.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.2
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• pp.55-60
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• 2020

In this paper, we propose a fast block matching algorithm of motion estimation using early detection of optimal candidate with high priority and a threshold. Even though so many fast algorithms for motion estimation have been published to reduce computational reduction full search algorithm, still so many works to improve performance of motion estimation are being reported. The proposed algorithm calculates block matching error for each candidate with high priority from previous partial matching error. The proposed algorithm can be applied additionally to most of conventional fast block matching algorithms for more speed up. By doing that, we can find the minimum error point early and get speed up by reducing unnecessary computations of impossible candidates. The proposed algorithm uses smaller computation than conventional fast full search algorithms with the same prediction quality as the full search algorithm. Experimental results shows that the proposed algorithm reduces 30~70% compared with the computation of the PDE and full search algorithms without any degradation of prediction quality and further reduces it with other fast lossy algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11C
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• pp.1091-1097
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• 2005

In this paper, we propose fast motion estimation algorithm. Local statistics of a motion vector is highly correlated to motion vectors of its neighboring blocks. According to the property, block-based motion search range is adaptively determined in order to reduce unnecessary search points. Based on the determined search range, motion vector is obtained by variable step search motion estimation. Experimental results show that comparing to Full search motion estimation, the motion searching points of proposed algorithm is reduced as much as $98\%$. Moreover, PSNR and Bit Rate are almost same to Full search method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.131-135
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• 1995

As the search range increases, most fast ME algorithms can not keep the performance comparable to the full search BMA. In this paper, we propose a new fast motion estimation method which locates the small search area for a block of the current frame. This method is based on interframe correlation of motion vectors as well as intraframe correlation. Especially, the proposed algorithm outperforms other fast methods when the motion is very fast or complex. It drastically reduces computational complexity while maintaining good performance compared with the conventional FS-BMA.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.389-391
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• 1999

영상 압축 기법에는 여러 가지 알고리즘을 적용되고 있다. 이런 알고리즘들에는 주파수 영역 중복을 제거하기 위한 DCT, 시간 중복성 제거를 위한 움직임 측정, 압축기법에 의해서 만들어진 정보를 부호화하는 VLC들이 있다. 이런 부호화 알고리즘들은 부호화기를 구현하는데 많은 시간을 요구하며 특히 움직임 추정은 부호화기의 절반에 가까운 시간을 소비한다. 움직임 측정 기술의 복잡도는 search algorithm, cost function, search range parameter의 요인으로 나타낼 수 있다. 본 논문에서는 기존의 Full Search 알고리즘 대신에 three-step 알고리즘을 사용하여 움직임 측정 시간을 줄였다. Full Search 알고리즘은 search area에서 모든 지역에 대해 cost function을 사용하여 이전 블록과 얼마나 유사한지를 조사한다. 따라서 이전 블록과 가장 유사한 부분을 찾는 좋은 방법이지만 그만큼 시간이 많이 사용한다. Three-step 알고리즘은 search area의 일정 지역에 대해 cost function를 사용하여 이전 블록과의 유사성을 찾는 fast 알고리즘이다. Three-step 알고리즘을 사용한 경우 기존의 full search 알고리즘을 사용할 때 보다 60% 정도의 시간이 단축되었다. 그리고 생성되는 압축 데이터의 크기는 full search 알고리즘을 사용할 때 보다 많이 차지한다. 생성되는 H.263파일의 화질에서는 Three-step 알고리즘을 사용한 경우일지라도 full search 알고리즘을 사용한 경우와 거의 비슷한 화질을 보여준다.

• 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.16 no.4
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• pp.129-133
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• 2015

In this paper, we propose a fast motion estimation algorithm which is important in the performance of video encoding. Conventional fast motion estimation algorithms have serious problems of low prediction quality in some frames and still much computation. In the paper, we propose an algorithm that reduces unnecessary computations only, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution of probability of motion vectors, divides search range into several groups according to its importance, and applies adaptive block matching criteria for each group of search range. The proposed algorithm takes only 3~5% in computational amount and has decreased prediction quality about 0~0.01dB compared with the fast full search algorithm.