• 제목/요약/키워드: adaptive orthogonal transformation

검색결과 3건 처리시간 0.022초

적응 직교변환을 이용한 LIFS 부호화의 고속화에 관한 연구 (A Study on fast LIFS Image Coding Using Adaptive Orthogonal Transformation)

  • 유현배;박경남;박지환
    • 한국멀티미디어학회논문지
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    • 제7권5호
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    • pp.658-667
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    • 2004
  • 영상 데이터의 압축을 위하여 영상이 갖고 있는 자기 유사성 (self similarity)을 이용하는 프랙탈 부호화가 활발하게 연구되고 있다. 본 연구에서는 부호화 효능에 있어서 JPEG과 경합이 가능한 적응 직교변환에 의한 LIFS 부호화에 주목하여 적응 직교변환의 연산 과정의 문제점을 지적하고 그 개선법을 제안하였다. 또한 직교변환의 모든 도메인(domain)을 포함하는 축소된 영상 데이터의 구성법을 제안하였다. 그 결과, 부호화 성능의 열화 없이도 부호기(encoder) 및 복호기(decoder)의 산술 연산량이 크게 삭감되었다.

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Computationally Efficient Lattice Reduction Aided Detection for MIMO-OFDM Systems under Correlated Fading Channels

  • Liu, Wei;Choi, Kwonhue;Liu, Huaping
    • ETRI Journal
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    • 제34권4호
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    • pp.503-510
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    • 2012
  • We analyze the relationship between channel coherence bandwidth and two complexity-reduced lattice reduction aided detection (LRAD) algorithms for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in correlated fading channels. In both the adaptive LR algorithm and the fixed interval LR algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for the adjacent highly correlated subcarriers. Complexity simulations demonstrate that the adaptive LR algorithm could eliminate up to approximately 90 percent of the multiplications and 95 percent of the divisions of the brute-force LR algorithm with large coherence bandwidth. The results also show that the adaptive algorithm with both optimum and globally suboptimum initial interval settings could significantly reduce the LR complexity, compared with the brute-force LR and fixed interval LR algorithms, while maintaining the system performance.

A New Adaptive Image Separation Scheme using ICA and Innovation Process with EM

  • Kim, Sung-Soo;Ryu, Jeong-Woong;Oh, Bum-Jin
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.96.2-96
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    • 2002
  • In this paper, a new method for the mixed image separation is presented using the independent component analysis, the innovation process, and the expectation-maximization. In general, the independent component analysis (ICA) is one of the widely used statistical signal processing scheme that represents the information from observations as a set of random variables in the form of linear combinations of another statistically independent component variables. In various useful applications, ICA provides a more meaningful representation of the data than the principal component analysis through the transformation of the data to be quasi-orthogonal to each other, which can be utilized in linear p...

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