数字图像的NLEMD分层压缩研究
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A New Multi–layered Digital Image Compressing Approach Based on NLEMD
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    摘要:

    二维限邻域经验模式分解(NLEMD)通过设定最大邻域(时宽)和采用邻域内局部自适应均值算法代替包络均值算法对图像进行分解,克服了以往EMD分解算法出现的灰度斑现象,改善了分解图像的质量。采用NLEMD算法进行图像分解,并基于当前普遍使用的JPEG图像压缩标准提出了数字图像分层压缩的算法。实验结果表明本文算法在确保重构图像较高质量的前提下,各层图像都实现了较高的压缩比率,对图像的分层压缩与传输的实现具有较高的实用价值。

    Abstract:

    Neighborhood limited empirical mode decomposition (NLEMD) is one novel time-frequency analysis tool which has the adaptive features and meanwhile adopts neighborhood limited (max time-width) to overcome other EMD’s gray spots in images , and enhances images. This paper adopts NLEMD to decompose images ,and , at the same time , proposes a new multi-layered image compressing approach based on JPEG which is the most popular image compression standard . The experiment result shows that this approach can keep the quality of images , and compress each layer to a good ratio . So it is useful in multi-layered image compressing and transmission.

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兰国辉,王秀森,胡程鹏. 数字图像的NLEMD分层压缩研究[J]. 科学技术与工程, 2011, (26): .
Lan Guo Hui,王秀森,胡程鹏. A New Multi–layered Digital Image Compressing Approach Based on NLEMD[J]. Science Technology and Engineering,2011,(26).

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  • 收稿日期:2011-06-02
  • 最后修改日期:2011-06-02
  • 录用日期:2011-06-08
  • 在线发布日期: 2011-08-04
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