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  1. (1. 西安电子科技大学 理学院,陕西 西安 710071;
    2. 桂林电子科技大学 数学与计算机科学学院, 广西 桂林 541004)
  • 收稿日期:2007-12-15 修回日期:1900-01-01 出版日期:2008-12-20 发布日期:2008-12-20
  • 通讯作者: 陈利霞

Image de-noising algorithm based on total variation and wavelet transform

CHEN Li-xia1,2;DING Xuan-hao2;SONG Guo-xiang1;SUN Xiao-li1

  1. (1. School of Science, Xidian Univ., Xi’an 710071, China;
    2. School of Mathematics and Computer Sci., Guilin Univ. of Eelectronic Tech., Guilin 541004, China)
  • Received:2007-12-15 Revised:1900-01-01 Online:2008-12-20 Published:2008-12-20
  • Contact: CHEN Li-xia

摘要: 针对标准的ROF模型在去噪时边缘信息对噪声敏感且易模糊的缺陷,提出了一种改进的图像去噪新方法.在新算法中引入各向异性的扩散函数,并利用小波变换的模替代梯度算子的模来检测图像的边缘,从而使新模型具有很好的鲁棒性并根据图像的特征进行平滑,因而更好的保护边缘信息.数值实验表明,新算法使峰值信噪比平均提高约1.5dB,在视觉效果上也有很大改善.

关键词: ROF模型, 图像去噪, 小波扩散

Abstract: Based on the standard ROF model, an improved method for image de-noising is proposed. In order to overcome the weakness that edge information is sensitive to noise and prone to blur of the ROF model while de-noising, in the new algorithm, the anisotropic diffusion function is introduced, and the magnitude of wavelet transform is substituted for the module of the gradient operator, which makes the new model more robust and diffuse according to the characteristic of the image, and therefore, the edges are preserved better. Experiments show that there is an increase of about 1.5dB on average in the signal to noise ratio and a remarkable improvement on the visual effect.

Key words: ROF model, image de-noising, wavelet diffusion


  • TP391