首页> 外文会议>International Conference on Measurement, Information and Control >The equivalence conditions of Wavelet Shrinkage and Anisotropic Diffusion and it's application in denosing
【24h】

The equivalence conditions of Wavelet Shrinkage and Anisotropic Diffusion and it's application in denosing

机译:小波收缩的等效条件和各向异性扩散及其在去噪中的应用

获取原文

摘要

The Wavelet Shrinkage distinguish between signals and noises according to their wavelet coefficient's amplitude, thus removing noises from noised signals by means of shrinkage. Anisotropic Diffusion diffuse signals according to gradient's direction and amplitude by different degree at different direction, removing the noises from noised signals while protecting signals. In this paper, the equivalence condition of Wavelet Shrinkage and Anisotropic Diffusion was proposed. Then the signals denoising algorithm based on the equivalence of Wavelet Shrinkage and Anisotropic Diffusion was proposed. The results show that the new algorithm combines the advantage of Wavelet Shrinkage and Anisotropic Diffusion, therefore it possesses the better ability of denoising and keeping the high frequency property of signals.
机译:小波收缩根据它们的小波系数的幅度区分信号和噪声,从而通过收缩从中断信号中除去噪声。各向异性扩散根据梯度方向和幅度的不同程度在不同方向上的幅度扩散信号,在保护信号的同时从中断信号中移除噪声。在本文中,提出了小波收缩和各向异性扩散的等效条件。然后提出了基于小波收缩等同物和各向异性扩散的去噪算法。结果表明,新算法结合了小波收缩和各向异性扩散的优势,因此它具有更好的去噪和保持信号的高频性能。

著录项

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