计算机科学 ›› 2009, Vol. 36 ›› Issue (5): 254-256.

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基于剪切不变的递归Contourlet变换图像去噪

  

  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60703117),国家自然科学基金项目(60703109)资助.

  • Online:2018-11-16 Published:2018-11-16

摘要: 根据综合剪切和递归Cycle Spinning技术,提出一种基于剪切不变的递归Contourlet变换图像去噪方法(RSICT)。为改善图像去噪由于缺少平移不变性而产生的伪吉布斯效应,使用剪切替代平移技术来提取图像中原有的几何特征,将递归Cycle Spinning方法运用在剪切技术中给出剪切不变思想,并将其用于Contourlet域图像去噪。对于被加性高斯白噪声污染的图像,实验中将RSICT方法与平移不变小波、平移不变Contourlet等方法进行了比较,结果表明在大多数情况下,RSICT的PSNR结果

关键词: 平移不变 剪切不变 Contourlet变换 递归Cycle Spinning

Abstract: Based on Shear and Recursive Cycle Spinning,a novel contourlet transform denoising scheme was proposed. To avoid the Gibbs-like phenomena caused by transform variance of the contourlet transform, translation method was replaced by shear technique and empl

Key words: Shear invariant, Translation invariant, Contourlet transform, Recursive cycle spinning

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