改进离散格子玻尔兹曼方法的图像去噪

于宁宁

doi:10.3788/YJYXS20173204.0294

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改进离散格子玻尔兹曼方法的图像去噪

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- 改进离散格子玻尔兹曼方法的图像去噪
- Image denoising based on modified discrete lattice Boltzmann method
- 液晶与显示 2017年32卷第4期页码：294-301
- 作者机构：
  
  浙江越秀外国语学院网络传播学院, 浙江绍兴 312000
- 作者简介：
  
  于宁宁(1978-)女,山东烟台人,硕士,讲师,研究方向:图像处理与模式识别。E-mail:dingningning1978@sina.com
- 基金信息：
- DOI：10.3788/YJYXS20173204.0294
  中图分类号： TP391
- 收稿日期：2016-10-20，
  
  录用日期：2016-12-7，
  
  纸质出版日期：2017-04
- 稿件说明：
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于宁宁. 改进离散格子玻尔兹曼方法的图像去噪[J]. 液晶与显示, 2017,32(4):294-301.

Ning-ning YU. Image denoising based on modified discrete lattice Boltzmann method[J]. Chinese journal of liquid crystals and displays, 2017, 32(4): 294-301.
于宁宁. 改进离散格子玻尔兹曼方法的图像去噪[J]. 液晶与显示, 2017,32(4):294-301. DOI： 10.3788/YJYXS20173204.0294.

Ning-ning YU. Image denoising based on modified discrete lattice Boltzmann method[J]. Chinese journal of liquid crystals and displays, 2017, 32(4): 294-301. DOI： 10.3788/YJYXS20173204.0294.

摘要

为解决生物医学图像处理过程中存在的图像反差低下且噪声污染严重等问题，本文对离散格子玻尔兹曼方法进行了改进，提出了一种改进离散格子玻尔兹曼方法的图像去噪算法。算法对分段线性拉伸函数进行构造，并作为LBM公式的外力因子，构建演化求解方程，通过调节变化因子

，同步控制图像降噪与反差增强的相关程度，消除降噪与反差增强之间的对立；通过优化平衡分布加权系数，折中扩散方程的求解精度和速度；将边缘特征和迭代步长嵌入松弛因子中，实现医学图像非线性扩散的去噪，解决医学图像处理中的同步降噪与反差增强间的矛盾。仿真实验表明，该算法与其他降噪算法相比，在有效抑制噪声的同时，细节处理更为有效。

Abstract

In order to solve the problem of low image contrast and serious noise pollution in the process of biomedical image processing

a modified lattice Boltzmann method is proposed. The algorithm structures the piecewise linear stretching function

and constructed it as the external force factor of the LBM formula to build the evolution equation. The algorithm adjusts the change factor

to synchronously control the correlation between image noise reduction and contrast enhancement to eliminate the contrast between noise reduction and contrast enhancement. By optimizing the weighting coefficients of the equilibrium distribution

the solution accuracy and speed of the tradeoff diffusion equation are obtained. The edge feature and the iterative step are embedded in the relaxation factor to realize the non-linear diffusion denoising of the medical image and to solve the contradiction between the synchronous noise reduction and the contrast enhancement in the medical image processing. The simulation results show that the proposed algorithm is more effective than other noise reduction algorithms in suppressing noise effectively.

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