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首页> 外文期刊>Optical engineering >Computation-aware algorithm selection approach for interlaced-to-progressive conversion
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Computation-aware algorithm selection approach for interlaced-to-progressive conversion

机译：隔行到渐进转换的计算感知算法选择方法

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摘要

We discuss deinterlacing results in a computationally constrained and varied environment. The proposed computation-aware algorithm selection approach (CASA) for fast interlaced to progressive conversion algorithm consists of three methods: the line-averaging (LA) method for plain regions, the modified edge-based line-averaging (MELA) method for medium regions, and the proposed covariance-based adaptive deinterlacing (CAD) method for complex regions. The proposed CASA uses two criteria, mean-squared error (MSE) and CPU time, for assigning the method. We proposed a CAD method. The principle idea of CAD is based on the correspondence between the high and low-resolution covariances. We estimated the local covariance coefficients from an interlaced image using Wiener filtering theory and then used these optimal minimum MSE interpolation coefficients to obtain a deinterlaced image. The CAD method, though more robust than most known methods, was not found to be very fast compared to the others. To alleviate this issue, we proposed an adaptive selection approach using a fast deinterlacing algorithm rather than using only one CAD algorithm. The proposed hybrid approach of switching between the conventional schemes (LA and MELA) and our CAD was proposed to reduce the overall computational load. A reliable condition to be used for switching the schemes was presented after a wide set of initial training processes. The results of computer simulations showed that the proposed methods outperformed a number of methods presented in the literature.
机译：我们讨论了在计算受限和变化的环境中的去隔行结果。所提出的用于快速隔行到逐行转换算法的计算感知算法选择方法（CASA）包含三种方法：用于平原区域的线平均（LA）方法，用于中等区域的改进的基于边缘的线平均（MELA）方法，以及针对复杂区域提出的基于协方差的自适应去隔行（CAD）方法。建议的CASA使用两个标准（均方误差（MSE）和CPU时间）来分配方法。我们提出了一种CAD方法。 CAD的基本思想是基于高分辨率和低分辨率协方差之间的对应关系。我们使用维纳滤波理论从隔行图像中估计局部协方差系数，然后使用这些最佳最小MSE插值系数来获得去隔行图像。尽管CAD方法比大多数已知方法都更可靠，但与其他方法相比并没有很快。为了缓解这个问题，我们提出了一种使用快速去隔行算法而不是仅使用一种CAD算法的自适应选择方法。提出了在常规方案（LA和MELA）和我们的CAD之间切换的混合方法，以减少总体计算量。经过广泛的初始培训过程后，提出了用于切换方案的可靠条件。计算机仿真结果表明，所提出的方法优于文献中提出的许多方法。

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  • 来源
    《Optical engineering》 |2010年第5期|p.057005.1-057005.9|共9页
  • 作者

    Sang-Jun Park; Gwanggil Jeon; Jechang Jeong;

  • 作者单位

    Hanyang University Department of Electronics and Computer Engineering 17 Haengdang-dong Seongdong-gu, Seoul, Korea;

    University of Ottawa School of Information Technology and Engineering (SITE) 800 King Edward, P.O. Box 450 Ottawa, Ontario K1N 6N5 Canada;

    Hanyang University Department of Electronics and Computer Engineering 17 Haengdang-dong Seongdong-gu, Seoul, Korea;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    covariance-based interpolation; deinterlacing; computation-aware system; fuzzy rule;

    机译：基于协方差的插值去隔行计算感知系统;模糊规则;

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