• Title/Summary/Keyword: Successive elimination algorithm

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Fast motion estimation scheme based on Successive Elimination Algorithm for applying to H.264 (H.264에 적용을 위한 SEA기반 고속 움직임 탐색 기법)

  • Lim Chan;Kim Young-Moon;Lee Jae-Eun;Kang Hyun-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.2 s.302
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    • pp.151-160
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    • 2005
  • In this paper, we propose a new fast motion estimation algorithm based on successive elimination algorithm (SEA) which can dramatically reduce heavy complexity of the variable block size motion estimation in H.264 encoder. The proposed method applies the conventional SEA in the hierarchical manner to the seven block modes. That is, the proposed algorithm can remove the unnecessary computation of SAD by means of the process that the previous minimum SAD is compared to a current SAD for each mode which is obtained by accumulating sum norms or SAD of $4\times4$ blocks. As a result, we have tighter bound in the inequality between SAD and sum norm than in the ordinary SEA. If the basic size of the block is smaller than $4\times4$, the bound will become tighter but it also causes to increase computational complexity, specifically addition operations for sum norm. Compared with fast full search algorithm of JM of H.264, our algorithm saves 60 to $70\%$ of computation on average for several image sequences.

Motion Adaptive Lossy Strict Multi-level Successive Elimination Algorithm for Fast Motion Estimation (고속 움직임 예측을 위한 움직임 적응적 손실성 엄격 다단계 연속 제거 알고리즘)

  • Lee, Kyung-Jun;Ng, Teck Sheng;Yoo, Jong-Sang;Jeong, Je-Chang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.11a
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    • pp.180-183
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    • 2012
  • 본 논문에서는 고속 움직임 예측(Fast Motion Estimation)방법의 일종인 다단계 연속 제거 알고리즘(MSEA : Multi-level Successive Elimination Algorithm)에 움직임의 역동성 정도를 고려하여 적응적인 가중치를 적용하는 방안에 대해 제안하였다. 움직임을 예측하는 과정에서 영상의 화질 손상이 발생하는 방식(Lossy Motion Estimation Algorithm)에서 모든 단위 블록(Macro Block)에 고정된 가중치만을 적용하는 기존의 방식과 달리 주위 블록의 움직임 벡터(Motion Vector)를 통해 움직임의 정도를 가정하여 적응적인 가중치를 적용함으로써 화질 손상을 줄이는 것이 목적이다. 제안하는 알고리즘으로 설계한 실험으로부터 MSEA에 적응적 가중치를 사용할 경우의 효율성을 확인하였다.

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An Adaptive and Fast Motion Estimation Algorithm using Initial Matching Errors (초기 매칭 에러를 통한 적응적 고속 움직임 예측 알고리즘)

  • Jeong, Tae-Il
    • 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.

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An Adaptive Multilevel Successive Elimination Algorithm (적응적 다단계 연속 제거 알고리즘)

  • Ahn, Tae-Gyoung;Moon, Yong-Ho;Kim, Jae-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.1C
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    • pp.111-118
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    • 2004
  • In this paper, an adaptive multilevel successive algorithm is presented. The algorithm introduces an adaptive initial level scheme to the conventional multilevel successive algorithm (MSEA). It efficiently removes the unnecessary computations required for judging the invalid candidate blocks at redundant level. The simulation results show that the proposed algorithm obtains the optimal motion vector with reduced computations compared to MSEA.

Block Matching Motion Estimation Using Fast Search Algorithm (고속 탐색 알고리즘을 이용한 블록정합 움직임 추정)

  • 오태명
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.3
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    • pp.32-40
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    • 1999
  • In this paper, we present a fast block matching motion estimation algorithm based on successive elimination algorithm (SEA). Based on the characteristic of center-biased motion vector distribution in the search area, the proposed method improves the performance of the SEA with a reduced the number of the search positions in the search area, In addition, to reduce the computational load, this method is combined with both the reduced bits mean absolute difference (RBMAD) matching criterion which can be reduced the computation complexity of pixel comparison in the block matching and pixel decimation technique which reduce the number of pixels used in block matching. Simulation results show that the proposed method provides better performance than existing fast algorithms and similar to full-search block motion estimation algorithm.

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A fast motion estimation method prediction of motion estimation error (움직임 추정오차의 예측을 이용한 고속 움직임 추정 방법)

  • Kang, Hyun-Soo
    • 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.

Optimal Measurement System Design by Using Band Matrix (밴드행열을 이용한 최적측정점선정에 관한 연구)

  • Song, Kyung-Bin;Choi, Sang-Bong;Moon, Toung-Hyun
    • Proceedings of the KIEE Conference
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    • 1987.11a
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    • pp.133-136
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    • 1987
  • This paper presents a new algorithm of optimal measurement system by using band matrix characteristic respectively for state estimation. A performance index of measurement system is established to reflect relation among measurement sets, probability of measurement failure and cost of individual meter installation. Selection ranking in the candidates of measurement sets is composed to guarantee the observability for any any single meter outage. Performance index sensitivity is introduced and recursive formula which based on the matrix inversion lemma used for selection. The proposed algorithm is composed of successive addition algorithm, successive elimination algorithm and combinatorial algorithm. The band matrix characteristic could save in memory requirements and calculate the performance index faster than earlier.

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A Fast Block Sum Pyramid Algorithm (빠른 블록 합 피라미드 알고리즘)

  • 정수목
    • The Journal of the Korea Contents Association
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    • v.3 no.4
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    • pp.11-16
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    • 2003
  • In this paper, a Fast Block Sum Pyramid Algorithm (FBSPA) is presented for motion estimation in video coding. PBSPA is based on Block Sum Pyramid Algorithm(BSPA), Efficient Multilevel Successive Elimination Algorithms for Block Matching Motion Estimation, and Fast Algorithms for the Estimation of Motion Vectors. FBSPA reduces the computations for motion estimation of BSPA 29% maximally using partial distortion elimination(PDE) scheme.

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Fast Motion Estimation Using Efficient Selection of Initial Search Position (초기 탐색 위치의 효율적 선택에 의한 고속 움직임 추정)

  • 남수영;김석규;임채환;김남철
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.167-170
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    • 2000
  • In this paper, we present a fast algorithm for the motion estimation using the efficient selection of an initial search position. In the method, we select the initial search position using the motion vector from the subsmpled images, the predicted motion vector from the neighbor blocks, and the (0,0) motion vector. While searching the candidate blocks, we use the spiral search pattern with the successive elimination algorithm(SEA) and the partial distortion elimination(PDE). The experiment results show that the complexity of the proposed algorithm is about 2∼3 times faster than the three-step search(TSS) with the PSNR loss of just 0.05[dB]∼0.1[dB] than the full search algorithm PSNR. The search complexity can be reduced with quite a few PSNR loss by controling the number of the depth in the spiral search pattern.

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