An advanced hierarchical motion estimation scheme with lossless frame recompression and early-level termination for beyond high-definition video coding

Xuena Bao, Dajiang Zhou, Peilin Liu, Satoshi Goto

    研究成果: Article

    24 被引用数 (Scopus)

    抄録

    In this paper, we present a hardware-efficient fast algorithm with a lossless frame recompression scheme and early-level termination strategy for large search range (SR) motion estimation (ME) utilized in beyond high-definition video encoder. To achieve high ME quality for hierarchical motion search, we propose an advanced hierarchical ME scheme which processes the multiresolution motion search with an efficient refining stage. This enables high data and hardware reuse for much lower bandwidth and memory cost, while achieving higher ME quality than previous works. In addition, a lossless frame recompression scheme based on this ME algorithm is presented to further reduce bandwidth. A hierarchical memory organization as well as a leveling two-step data fetching strategy is applied to meet constraint of random access for hierarchical motion search structure. Also, the leveling compression strategy by allowing a lower level to refer to a higher one for compression is proposed to efficiently reduce the bandwidth. Furthermore, an early-level termination method suitable for hierarchical ME structure is also applied. This method terminates high-level redundant motion searches by establishing thresholds based on current block mode and motion search level; it also applies the early refinement termination in order to avoid unnecessary refinement for high levels. Experimental results show that the total scheme has a much lower bit rate increasing compared with previous works especially for high motion sequences, while achieving a considerable saving of memory and bandwidth cost for large SR of [-128,127].

    本文言語English
    論文番号6043909
    ページ(範囲)237-249
    ページ数13
    ジャーナルIEEE Transactions on Multimedia
    14
    2
    DOI
    出版ステータスPublished - 2012 4

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Signal Processing
    • Media Technology
    • Computer Science Applications

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