• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.750-755
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• 1998

Due to the temporal spatial correlation of the image sequence, the motion vector of a block is highly related to the motion vectors of its adjacent blocks in the same image frame. If we can obtain useful and enough information from the adjacent motion vectors, the total number of search points used to find the motion vector of the block may be reduced significantly. Using that idea, an efficient fuzzy prediction search (FPS) algorithm for block motion estimation is proposed in this paper. Based on the fuzzy inference process, the FPS can determine the motion vectors of image blocks quickly and correctly.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.217-220
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• 1996

This paper describes a new hierarchial block matching algorithm especially appropriate for a large search area. The proposed algorithm consists of higher level search for an initial motion vector estimate by using a new matching criterion over the evenly subsampled search points, and lower level search for the final motion vector refinement. In the higher level matching criterion, mean absolute differences at the search points (or motion vector candidates) similar to motion vectors of causally neighboring blocks, are weighted properly so that these points can have a higher chance to being selected. The proposed algorithm outperforms existing hierarchical block matching algorithms, and its computational regularity makes hardware implementation simple.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1392-1400
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• 1999

In this paper, we propose a two-stage fast full search algorithm for block motion estimation that produces the same performance to that of full search algorithm (FSA) but with remarkable computation reduction. The proposed algorithm uses the search region subsampling and the difference of adjacent pixels in the current block. In the first stage, we subsample the search region by a factor of 9, and then calculate mean absolute error (MAE) at the subsampled search points. And in the second stage, we reduce the search points that need block matching process by using the lower bound of MAE value at each search Point. We Set the lower bound of MAE value for each search point from the MAE values which are calculated at the first stage and the difference of adjacent pixels in the current block. The experimental results show that we can reduce the computational complexity considerably without any degradation of picture quality.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.57-65
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• 2007

In the fast block matching algorithm. search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image qualify. In this paper, we propose a new fast block matching algorithm using the flat-hexagon search pattern that ate solved disadvantages of the diamond pattern search algorithm(DS) and the hexagon-based search algorithm(HEXBS). Our proposed algorithm finds mainly the motion vectors that not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the DS and HEXBS, the proposed f)at-hexagon search algorithm(FHS) improves about $0.4{\sim}21.3%$ in terms of average number of search point per motion vector estimation and improves about $0.009{\sim}0.531dB$ in terms of PSNR(Peak Signal to Noise Ratio).

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.13-20
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• 2003

Based on the studies on the motion vector distributions estimated on the image sequences, we proposed constrained diamond search (DS) algorithm for fast block-matching motion estimation. By considering the fact that motion vectors are searched within the 2 pixels distance in vertically and horizontally on average, we confirmed that DS algorithm achieves close performance on error ratio and requires less computation compared with new three-step search (NTSS) algorithm. Also, by applying displaced frame difference (DFD) to DS algorithm, we reduced the computational loads needed to estimate the motion vectors within the stable block that do not have motions. And we reduced the possibilities falling into the local minima in the course of estimation of motion vectors by applying DFD to DS algorithm. So, we knew that proposed constrained DS algorithm achieved enhanced results as aspects of error ratio and the number of search points to be necessary compared with conventional DS algorithm, four step search (FSS) algorithm, and block-based gradient-descent search algorithm

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.885-888
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• 2000

Among the previous searching methods, there are the typical methods such as full search and three-step search, etc. Block motion estimation using exhaustive search is too computationally intensive. To apply in practice, recently proposed fast algorithms have been focused on reducing the computational complexity by limiting the number of searching points. According to the reduction of searching points, the quality performance is aggravated in those algorithms. In this paper, We present a fast and efficient search algorithm for block motion estimation that produces better quality performance and less computational time compared with a three-step search (TSS). Previously the proposed Two Step Search Algorithm (TWSS) by Fang-Hsuan Cheng and San-Nan sun is based on the ideas of dithering pattern for pixel decimation using a part of a block pixels for BMA (Block Matching Algorithm) and multi-candidate to compensate quality performance with several locations. This method has good quality performance at slow moving images, but has bad quality performance at fast moving images. To resolve this problem, the proposed algorithm in this paper considers spatial and temporal correlation using neighbor and previous blocks to improve quality performance. This performance uses neighbor motion vectors and previous motion vectors in addition, thus it needs more searching points. To compensate this weakness, the proposed algorithm uses statistical character of dithering matrix. The proposed algorithm is superior to TWSS in quality performance and has similar computational complexity

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1604-1608
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• 2000

The three-step search (TSS) algorithm for block motion estimation has been widely used in real-time video coding due to the simplicity of the algorithm significant reduction of computationl cost and good performance. In this paper an improved three-step search (ITS) algorithm is proposed to improve the performance of the TSS algorithm. Simulation results show that in terms of motion compensation errors the proposed ITSS outperforms some popular fast search algorithms while it has the lower computational complexity.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.317-326
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• 2002

The adaptive coding schemes in H.264 standardization provide a significant ceding efficiency and some additional features like error resilience and network friendliness. The variable block size motion compensation using multiple reference frames is one of the key H.264 coding elements to provide main performance gain, but also the main culprit that increases the overall computational complexity. For this reason, this paper proposes a selective motion estimation algorithm based on variable block size for fast motion estimation in H.264. After we find the SAD(Sum of Absolute Difference) at initial points using diamond search, we decide whether to perform additional motion search in each block. Simulation results show that the proposed method is five times faster than the conventional full search in case of search range $\pm$32.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.131-139
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• 2007

This paper proposed a multi-resolution algorithm. Its search point and complexity were compared with those of block match algorithm. Also the speed up comparison was made with the block match algorithm. The proposed multi-resolution NTSS-3 Level algorithm was compared again with its targets, TSS-3 Level algorithm and NTSS algorithm. The comparison results showed that the NTSS-3 Level algorithm was superior in search point and speed up. Accordingly, the proposed NTSS-3 Level algorithm was two to three times better in search point and two to four times better in complexity calculation than those of the compared object, the block match algorithm. In speed up, the proposed NTSS-3 Level algorithm was two times better. Accordingly, the proposed multi-resolution NTSS-3 Level algorithm showed PSNR ration portion excellency in search point and speed up.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.966-974
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• 1999

완전 탐색 블록 정합 알고리즘(FBMA)은 다양한 움직임 추정 알고리즘 중 최상의 움직임 추정을 할 수 있으나, 방대한 계산량이 실시간 처리의 적용에 장애 요소이다. 본 논문에서는 완전 탐색 블록 정합 알고리즘에 비해 더 낮은 계산량과 유사한 화질을 가지는 새로운 고속 움직임 추정 알고리즘을 제안한다. 제안한 방법에서는 공간적인 상관성을 이용함으로써 적절한 탐색 영역의 크기를 예측할 수 있다. 현재 블록의 움직임 추정을 위하여 이웃 블록이 가지고 있는 움직임과 탐색 영역의 크기를 이용하여 현재 블록의 탐색 영역을 적응적으로 변화시키는 방법이다. 이 예측값으로 현재 블록의 탐색 영역 크기를 결정한 후, FBMA와 같이 이 영역 안의 모든 화소점들에 대하여 현재 블록을 정합하여 움직임 벡터를 추정한다. 컴퓨터 모의 실험 결과 계산량 측면에서 제안 방법이 완전 탐색 블록 정합 알고리즘보다 50%정도 감소하였으며, PSNR 측면에서는 0.08dB에서 1.29dB 정도 감소하는 좋은 결과를 얻었다.Abstract Full search block-matching algorithm (FBMA) was shown to be able to produce the best motion compensated images among various motion estimation algorithms. However, huge computational load inhibits its applicability in real applications. A new motion estimation algorithm with lower computational complexity and good image quality when compared to the FBMA will be presented in this paper. In the proposed method, The appropriate search area can be predicted by using the temporal correlation between neighbouring blocks. For motion estimation of the current block, it is the method changing adjustably search area of current block by using motion and search area size of the neighbouring block. After deciding search area size of the current block with this predicted value, we estimate motion vector that matching current block like the FBMA for every pixel in this area. By the computer simulation the computation amount of the proposed method can be greatly decreased about 50% than that of the FBMA and the good result of the PSNR can be attained.