• Title/Summary/Keyword: AZCB

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Enhanced Adaptive Mode Decision of H.264 Based on Efficient AZCB Prediction (능률적 AZCB 예측 기반 H.264 적응 모드 결정 개선 알고리즘)

  • Kim, Yang-Soo;Kim, Yong-Goo;Choe, Yoon-Sik;Choi, Yung-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.11
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    • pp.2036-2039
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    • 2007
  • This paper proposes an enhanced adaptive mode decision scheme for fast H.264 encoders. By efficiently predicting AZCB (All Zero Coefficient Block), the proposed scheme can encode motion pictures in H.264 up to 2.86 and 1.68 times faster than JM9.3 and AMD [1], respectively. Besides, this scheme significantly reduces the encoding performance fluctuation of AMD across tested bit-rates and video sequences.

An Effective Mode Decision Algorithm in H.264/AVC Encoder (H.264/AVC 부호화기에 대한 효과적인 모드 결정 알고리즘)

  • Moon Jeong-Mee;Kim Jae-Ho;Moon Yong-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.3C
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    • pp.250-257
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    • 2006
  • In this paper, we propose an efficient algorithm for the RDO mode decision in H.264/AVC encoder. Based on the properties of DCT coefficients and the RDO mode decision processing, we derive a new condition for detecting an error block having all-zero DCT coefficient (AZCB). (I)DCT, (I)Q, and entropy coding are skipped for AZCBs in the proposed algorithm. It makes the reduction of the computational complexity for the RDO mode decision. Simulation results show that the proposed algorithm achieves computational saving over 40% compared to the conventional method.

Fast Multiple Reference Frame Selection for H.264 Encoding (H.264 부호화를 위한 고속 다중 참조 화면 결정 기법)

  • Jeong, Jin-Woo;Cheo, Yoon-Sik
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.419-420
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    • 2006
  • In the new video coding standard H.264/AVC, motion estimation (ME) is allowed to search multiple reference frames for improve the rate-distortion performance. The complexity of multi-frame motion estimation increases linearly with the number of used reference frame. However, the distortion gain given by each reference frame varies with the video sequence, and it is not efficient to search through all the candidate frames. In this paper, we propose a fast mult-frame selection method using all zero coefficient block (AZCB) prediction and sum of difference (SAD) of neighbor block. Simulation results show that the speed of the proposed algorithm is up to two times faster than exhaustive search of multiple reference frames with similar quality and bit-rate.

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