Improved image denoising algorithm of PDEs based on fuzzy logic

doi:10.3778/j.issn.1002-8331.2009.10.008

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (10): 23-25.DOI: 10.3778/j.issn.1002-8331.2009.10.008

• 博士论坛 • Previous Articles Next Articles

Improved image denoising algorithm of PDEs based on fuzzy logic

SHI Zhen-gang^1,2,GAO Li-qun²

1.College of Information Science and Engineering，Shenyang Ligong University，Shenyang 110168，China
2.College of Information Science and Engineering，Northeastern University，Shenyang 110004，China

Received:2008-12-17 Revised:2009-02-09 Online:2009-04-01 Published:2009-04-01
Contact: SHI Zhen-gang

改进的模糊逻辑偏微分方程去噪方法

石振刚^1,2,高立群²

1.沈阳理工大学信息科学与工程学院，沈阳 110168
2.东北大学信息科学与工程学院，沈阳 110004

通讯作者: 石振刚

Abstract

Abstract: In research of image denoising，in order to remove noise effectively and preserve edges and key details，an effective image denoising algorithm based on fuzzy logic PDEs is proposed in this paper.This algorithm combines the fuzzy logical with the Perona-Malik method.This algorithm builds a new diffusion coefficient in partial derivative equation with the fuzzy membership between the image gradient and the corresponding smooth regions.By defining reasonable fuzzy membership function，the algorithm is based upon a selective and improved diffusion coefficient and performed adaptively towards different gradients.Simulation experiments show the algorithm can effectively reduce the noises of the image，and its results needn’t to be adjusted，which can enhance the precision of edge orientation.

Key words: noisy image, partial derivative equation, diffusion coefficient, fuzzy logic, fuzzy membership function

摘要： 在研究图像噪声过滤时，为了既有效地去除噪声，又能够较好地保持图像边缘和重要的细节信息，将模糊逻辑思想与PM方法相结合，提出了一种对噪声图像更有效的基于模糊逻辑的偏微分方程去噪算法。该算法把PM方法中扩散方程的扩散系数看作像素梯度对于图像平滑区域的模糊隶属度函数，并通过定义合理的模糊隶属度函数，使得对不同的像素梯度大小采用不同的扩散系数。仿真实验表明，此算法在去除噪声的同时，能更好地保持图像的边缘细节，具有较好的处理效果。

关键词: 噪声图像, 偏微分方程, 扩散系数, 模糊逻辑, 模糊隶属度函数

SHI Zhen-gang^1,2,GAO Li-qun². Improved image denoising algorithm of PDEs based on fuzzy logic[J]. Computer Engineering and Applications, 2009, 45(10): 23-25.

石振刚^1,2,高立群². 改进的模糊逻辑偏微分方程去噪方法[J]. 计算机工程与应用, 2009, 45(10): 23-25.

[1]	YUAN Shunjie, CHENG Hui, YE Zhencheng, CHENG Peixin. Application of SOM-T2 FLS in Stock Market Forecasting [J]. Computer Engineering and Applications, 2020, 56(7): 130-136.
[2]	WANG Lunlei, WU Hongbo. Annihilator operators and[⊕]ideals of IMTL-algebra with their relationships [J]. Computer Engineering and Applications, 2017, 53(9): 57-62.
[3]	LV Fengjie, XIN Ke. Blind noisy image quality assessment algorithm based on wavelet kurtosis [J]. Computer Engineering and Applications, 2017, 53(7): 202-205.
[4]	FANG Zheng, HU Xiaohui, CHEN Yong. Anisotropic diffusion wave filtering algorithm based on median filtering method in multi directions [J]. Computer Engineering and Applications, 2017, 53(4): 195-199.
[5]	LI Qing, ZHENG Lixin, PAN Shuwan, ZHANG Yukun, XIE Yishou. Method of mobile robot navigation using monocular vision [J]. Computer Engineering and Applications, 2017, 53(4): 223-227.
[6]	LIU Yi1，2, ZHANG Quan1，2, ZHANG Pengcheng1，2, SONG Shengtao1, CHEN Yang3, GUI Zhiguo1，2. Edge detection algorithm based on intuitionistic fuzzy divergence for noisy image [J]. Computer Engineering and Applications, 2017, 53(23): 6-11.
[7]	SHI Xiaojing, ZHANG Xingfang. Comparing of probabilistic logic, uncertain logic and fuzzy logic [J]. Computer Engineering and Applications, 2017, 53(12): 50-52.
[8]	PENG Yanfei, ZHOU Nan, LIN Sen. Improved SLTP feature extraction algorithm for palmprint recognition [J]. Computer Engineering and Applications, 2016, 52(5): 179-184.
[9]	ZHOU Jianren1，2, WU Hongbo2. Syntactic proof of equivalence between [BL?] system and IMTL system [J]. Computer Engineering and Applications, 2016, 52(5): 41-46.
[10]	LI Xu, LIU Zhengyan. Fuzzy self-adaptive ant colony algorithm based on cloud model [J]. Computer Engineering and Applications, 2016, 52(2): 24-27.
[11]	JI Lizhen1, LI Peng1, LI Lin2, LIU Chengyu1, WANG Xinpei1, LI Ke1, LIU Changchun1. Analysis of cardiac electro-mechanical time-series in patients with coronary artery disease based on entropy [J]. Computer Engineering and Applications, 2016, 52(10): 265-270.
[12]	LV Xinzhi. Theory and application of FAST-SR-UKF to integrated navigation systems [J]. Computer Engineering and Applications, 2015, 51(6): 254-259.
[13]	TAN Qiaoqiao, YANG Jiyun. Application of improved AR（p） prediction model in WSN [J]. Computer Engineering and Applications, 2015, 51(12): 83-87.
[14]	WANG Hongqi, MAO Amin. Robust and adaptive control of uncertain planar double inverted pendulum [J]. Computer Engineering and Applications, 2015, 51(11): 31-34.
[15]	HU Hui1, HE Juhou1，2, HE Xiuqing1. Edge linking method based on fuzzy theory and ant colony algorithm [J]. Computer Engineering and Applications, 2014, 50(3): 168-172.

Improved image denoising algorithm of PDEs based on fuzzy logic

改进的模糊逻辑偏微分方程去噪方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics