江苏省科技期刊可视化阅读平台

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江苏科技信息 ›› 2019, Vol. 36 ›› Issue (6): 31-33.doi: 10.1004-7530/2019-36-6-31

• 基础研究 • 上一篇    下一篇

基于TV模型的去噪算法改进

朱国远,任蒙蒙,朱美玲   

  1. 南京邮电大学通达学院,江苏 扬州 225127
  • 出版日期:2019-02-28 发布日期:2019-07-09
  • 作者简介:朱国远（1997— ）,男,江苏连云港人,本科生;研究方向：图像处理。

Improvement of denoising algorithm based on TV model

Guoyuan Zhu,Mengmeng Ren,Meiling Zhu   

  1. Tongda College, Nanjing University of Posts and Telecommunications, Yangzhou 225127, China
  • Online:2019-02-28 Published:2019-07-09

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摘要：

文章通过分析调和去噪模型、ROF模型、广义TV模型,提出了基于TV模型的去噪算法改进。在调和模型的基础上对扩散系数进行了改进,从而克服了ROF模型的阶梯效应。改进后的算法可以去除更多的噪声,同时保留了图像的边缘,且与ROF模型相比,在不同噪声下其峰值信噪比均能有一定的提升。

关键词: 图像去噪, 保留边缘, 全变分模型, 扩散系数

Abstract:

This paper proposes an improvement of the denoising algorithm based on TV model by analyzing the harmonic denoising model, ROF model and generalized TV model. The diffusion coefficient is improved on the basis of the harmonic model, thus overcoming the ladder effect of the ROF model. The improved algorithm can remove more noise while preserving the edge of the image, and its peak signal-to-noise ratio can be improved under different noises compared with the ROF model.

Key words: image denoising, preserved edge, total variation model, diffusion coefficient

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