Image Denoising Method and Evaluation Based on Mixed Wavelet Algorithm

被引：4
|
作者：
Shen Yanchun [1 ,2 ]
Zhao Guozhong [1 ]
Zhang Shengbo [1 ]
Li Shuai [1 ]
Li Yashang [1 ]
机构：
[1] Capital Normal Univ, Phys Dept, Minist Educ, Key Lab Terahertz Optoelect, Beijing 100048, Peoples R China
[2] Guangzhou Railway Polytech, Guangzhou 51430, Peoples R China
来源：
ELEVENTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2019) | 2019年 / 11179卷
基金：
中国国家自然科学基金;
关键词：
Mixed Wavelet Algorithm; Fourier Transform; Image Denoising; Wavelet Threshold Denoising;
D O I：
10.1117/12.2540098
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
The principle and evaluation method of wavelet threshold denoising are analyzed aiming at the problem that Fourier transform cannot represent the abrupt change of image effectively and wavelet transform cannot represent the texture and slow change of image effectively in the process of image denoising. Through the quantitative comparison of Fourier image denoising and wavelet image denoising, a mixed Fourier-wavelet denoising algorithm is proposed based on the different characteristics of Fourier denoising and wavelet denoising. Experimental results show that the mixed wavelet algorithm is superior to simple Fourier denoising and wavelet denoising algorithm separately, which makes up for the disadvantages of the two algorithms, and has a good application prospect in the field of image denoising.
引用
收藏
页数：6
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