• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.309-316
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• 2004

In this paper, we proposed the TDS(T-shape Diamond Search) based on the directions of above, below, left and right points to estimate the motion vector fast and more correctly in this method, we exploit the facts that most motion vectors are enclosed in a circular region with a radius of 2 fixels around search center(0,0). At first, the 4 points in the above, below, left and right around the search center is calculated to decide the point of the MBD(Minimum Block Distortion). And then w. above point of the MBD is checked to calculate the SAD. If the SAD of the above point is less than the previous MBD, this process is repeated. Otherwise, the right and left points of MBD are calculated to decide The points that have the MBD between right point and left point. Above processes are repeated to the predicted direction for motion estimation. Especially, if the motions of image are concentrated in the crossing directions, the points of other directions are omitted. As a result, we can estimate motion vectors fast. Experiments show that the speedup improvement of the proposed algorithm over Diamond Search algorithm(DS) and HEXgon Based Search(HEXBS) can be up to 38∼50％ while maintaining similar image Quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.54-63
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• 2000

We present a multi-resolution block matching algorithm (BMA) for fast motion estimation At the coarsest level, a motion vector (MV) having minimum matching error is chosen via a full search, and a MV with minimum matching error is concurrently found among the MVs of the spatially adjacent blocks Here, to examine the spatial MVs accurately, we propose an efficient method for searching full resolution MV s without MV quantization even at the coarsest level The chosen two MV s are used as the initial search centers at the middle level At the middle level, the local search is performed within much smaller search area around each search center If the method used at the coarsest level is adopted here, the local searches can be done at integer-pel accuracy A MV having minimum matching error is selected within the local search areas, and then the final level search is performed around this initial search center Since the local searches are performed at integer-pel accuracy at the middle level, the local search at the finest level does not take an effect on the overall performance So we can skip the final level search without performance degradation, thereby the search speed increases Simulation results show that in comparison with full search BMA, the proposed BMA without the final level search achieves a speed-up factor over 200 with minor PSNR degradation of 02dB at most, under a normal MPEG2 coding environment Furthermore, our scheme IS also suitable for hardware implementation due to regular data-flow.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.393-396
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• 2001

영상 압축 분야에서는 데이터 압축이 필수적인데, 이때 가장 많은 데이터 중복성을 가지고 있는 시간적 중복성은 이전 프레임의 데이터를 이용하여 움직임 추정과 움직임 보상을 수행하고 추정된 움직임 벡터에 의해서 보상된 영상과 원 영상과의 차 신호를 부호화하여 데이터를 압축한다. 움직임 추정과 움직임 보상기법은 비디오 영상압축에서 중요한 역할을 하지만 많은 계산량으로 인하여 실시간 응용이나 고해상도 응용에 많은 어려움을 가지고 있다. 이러한 문제점을 해결하기 위하여 여러 가지 고속정합 알고리즘들과 하드웨어 기법들이 개발되었다. 특히 다이아몬드 탐색 기법은 계산량도 줄이고 안정된 복원 영상 화질을 유지하고 있다. 본 논문에서는 기존의 다이아몬드 탐색 기법의 문제점을 개선한 수정된 다이아몬드 탐색 기법을 제안하고 성능을 평가한다. 실험에 의하여 제안된 기법은 기존의 다이아몬드 탐색 기법과 비교하여 화질 면에서나 속도 면에서 모두 좋은 결과를 가져왔다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.508-510
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• 2001

동영상을 효율적으로 압축하기 위한 움직임백터 예측에 관한 많은 연구가 진행되어 왔다. 가장 일반적인 FBMA(Full search-based Block Matching Algorithm)는 화질은 좋지만 계량이 많기 때문에 실시간 인코딩을 요구하는 시스템에서 사용하는데 문제가 있다. 좋은 화질을 유지하면서 인코딩 속도를 해결하기 위한 많은 알고리즘들이 제안되어 왔지만 ASIC이나 소형 시스템에서 사용할 수 있는 방법이 계속 요구되고 있다. 본 논문에서는 계산량을 더욱 줄여 속도향상을 위한 방법인 TSWS(Two-Step search With Subsampling method) 제안하였다. TSWS는 블록정합알고리즘에 기반을 두고 있으며, 서브샘플링한 값으로 움직임 벡터를 찾는다. TSWS를 사용하였을 때 기존 방법들이 제공하는 주관적 화질이나 PSNR을 어느 정도 유지하면서도 속도를 20-30% 정도 개선시킬 수 있다.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.305-315
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• 2008

Pre-proposed AHHS(Adaptive Hierarchical Hexagon Search) is a kind of the fast hierarchical block matching algorithm based on the AHS(Adaptive Hexagon Search). It is characterized as keeping the merits of the AHS capable of fast estimating motion vectors and also adaptively reducing the local minima often occurred in the video sequences with higher spatio-temporal motion activity. The objective of this paper is to propose the method effectively extending the horizontal biased pattern and the vertical biased pattern of the AHHS to improve its predictive image quality. In the paper, based on computer simulation results for multiple video sequences with different motion characteristics, the performance of the proposed method was analysed and assessed in terms of the predictive image quality and the computational time. The simulation results indicated that the proposed method was both suitable for (quasi-) stationary and large motion searches. While the proposed method increased the computational load on the process extending the hexagon search patterns, it could improve the predictive image quality so as to cancel out the increase of the computational load.