• Title/Summary/Keyword: 전역탐색 블럭정합 방식

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Low Power Motion Estimation Architecture for H.26L (H.26L 저전력 움직임 추정 구조)

  • 김태욱;김재호
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.701-704
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    • 2001
  • 본 논문은 영상압축 표준의 하나로 표준화가 진행중 인 H.26L에 효율적인 저전력 움직임 추정 구조를 제안한다. 제안하는 방식은 움직임 추정에 사용하는 이전 프레임에서의 움직임 벡터 발생 빈도와 경향을 이용하여 계산량과 수행시간을 줄인다. 그리고 가변 블럭 정합을 고려하여 먼저 최소 블럭 크기 단위로 블럭 SAD를 계산한 후 다른 모드 블럭 SAD 를 계산으로 생성한다. 제안하는 방식은 기존의 저전력 블럭 정합 방식과 비교하여 최대 31% 전력 소모 감소가 이루어지며 완전 전역 탐색 블럭 정합 방식에 비해 평균 75-90%의 계산량이 감소된다.

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VLSI Implementation of Low-Power Motion Estimation Using Reduced Memory Accesses and Computations (메모리 호출과 연산횟수 감소기법을 이용한 저전력 움직임추정 VLSI 구현)

  • Moon, Ji-Kyung;Kim, Nam-Sub;Kim, Jin-Sang;Cho, Won-Kyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5A
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    • pp.503-509
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    • 2007
  • Low-power motion estimation is required for video coding in portable information devices. In this paper, we propose a low-power motion estimation algorithm and 1-D systolic may VLSI architecture using full search block matching algorithm (FSBMA). Main power dissipation sources of FSBMA are complex computations and frequent memory accesses for data in the search area. In the proposed algorithm, memory accesses and computations are reduced by using 1D PE (processing array) array architecture performing motion estimation of two neighboring blocks in parallel and by skipping unnecessary computations during motion estimation. The VLSI implementation results of the algorithm show that the proposed VLSI architecture can save 9.3% power dissipation and can operate two times faster than an existing low-power motion estimator.

A fast block-matching algorithm using the slice-competition method (슬라이스 경쟁 방식을 이용한 고속 블럭 정합 알고리즘)

  • Jeong, Yeong-Hun;Kim, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.692-702
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    • 2001
  • In this paper, a new block-matching algorithm for standard video encoder is proposed. The algorithm finds a motion vector using the increasing SAD transition curve for each predefined candidates, not a coarse-to-fine approach as a conventional method. To remove low-probability candidates at the early stage of accumulation, a dispersed accumulation matrix is also proposed. This matrix guarantees high-linearity to the SAD transition curve. Therefore, base on this method, we present a new fast block-matching algorithm with the slice competition technique. The Candidate Selection Step and the Candidate Competition Step makes an out-performance model that considerably reduces computational power and not to be trapped into local minima. The computational power is reduced by 10%~70% than that of the conventional BMAs. Regarding computational time, an 18%~35% reduction was achieved by the proposed algorithm. Finally, the average MAD is always low in various bit-streams. The results were also very similar to the MAD of the full search block-matching algorithm.

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The FASCO BMA based on Motion Vector Prediction using Spatio-temporal Correlations (시공간적 상관성을 이용한 움직임 벡터 예측 기반의 FASCO 블럭 정합 알고리즘)

  • 정영훈;김재호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.11A
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    • pp.1925-1938
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    • 2001
  • In this paper, a new block-matching algorithm for standard video encoder is presented. The slice competition method is proposed as a new scheme, as opposed to a coarse-to-fine approach. The order of calculating the SAD(Sum of Absolute Difference) to fad the best matching block is changed from a raster order to a dispersed one. Based on this scheme, the increasing SAD curve during its calculation is more linear than that of other curves. Then, the candidates of low probability can be removed in the early stage of calculation. And new MV prediction technique with an adaptive search range scheme also assists the proposed block-matching algorithm. As a result, an average of 13% improvement in computational power is recorded by only the proposed MV prediction technique. Synthetically, the computational power is reduced by 3977∼77% than that of the conventional BMAs. The average MAD is always low in various sequences. The results are also very close to the MAD of the full search block-matching algorithm.

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