• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Multimedia Tools and Applications >Image denoising based on improved bidimensional empirical mode decomposition thresholding technology
【24h】

Image denoising based on improved bidimensional empirical mode decomposition thresholding technology

机译：基于改进的二维经验模态分解阈值技术的图像去噪

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, a novel image denoising methodology based on improved bidimensional empirical mode decomposition and soft interval thresholding technique is proposed. First, a noise compressed image is constructed. Then, the noise compressed image is decomposed by means of bidimensional empirical mode decomposition (BEMD) into a series of intrinsic mode functions (IMFs), which are separated into signal-dominant IMFs and noise-dominant IMFs using a similarity measure based on 2-norm and a probability density function, and a soft interval thresholding technique is used adaptively to remove the noise inherent in noise-dominant IMFs. Finally, a denoised image is reconstructed by combining the signal-dominant IMFs and the denoised noise-dominant IMFs. The performance of the proposed denoising method is evaluated by using multiple images with different types of noise, and results from the proposed method are compared with those of other conventional methods in various noisy environments. Simulation results demonstrate that the proposed denoising method outperforms other denoising methods in terms of peak signal-to-noise ratio, mean square error and energy of the first IMF.
机译：提出了一种基于改进的二维经验模态分解和软间隔阈值技术的图像去噪方法。首先，构造噪声压缩图像。然后，通过二维经验模式分解（BEMD）将噪声压缩图像分解为一系列固有模式函数（IMF），使用基于2的相似度度量将其分为信号主导型IMF和噪声主导型IMF。规范和概率密度函数，以及软间隔阈值技术被自适应地用于去除噪声占主导的IMF中固有的噪声。最后，通过组合信号主导型IMF和降噪主导型IMF来重建去噪图像。通过使用具有不同类型噪声的多幅图像来评估所提出的去噪方法的性能，并将所提出的方法的结果与在各种嘈杂环境中的其他常规方法的结果进行比较。仿真结果表明，所提出的去噪方法在峰值信噪比，均方误差和第一IMF的能量方面优于其他去噪方法。

著录项

  • 来源
    《Multimedia Tools and Applications》 |2019年第6期|7381-7417|共37页
  • 作者

    Liu Di; Chen Xiyuan;

  • 作者单位

    Southeast Univ, Sch Instrument Sci & Engn, Minist Educ, Key Lab Microinertial Instrument & Adv Nav Techno, Nanjing 210096, Jiangsu, Peoples R China;

    Southeast Univ, Sch Instrument Sci & Engn, Minist Educ, Key Lab Microinertial Instrument & Adv Nav Techno, Nanjing 210096, Jiangsu, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    BEMD; Image denoising; Noise compression;

    机译：BEMD;图像去噪;噪声压缩;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号