[1]李晓飞,邱晓晖. 基于小波变换的改进软阈值图像去噪算法[J].计算机技术与发展,2016,26(05):76-78.
　LI Xiao-fei,QIU Xiao-hui. An Improved Soft-threshold Image Denoising Algorithm Based on Wavelet Transform[J].,2016,26(05):76-78.
点击复制

 基于小波变换的改进软阈值图像去噪算法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年05期
页码:
76-78
栏目:
智能、算法、系统工程
出版日期:
2016-05-10

文章信息/Info

Title:
 An Improved Soft-threshold Image Denoising Algorithm Based on Wavelet Transform
文章编号:
1673-629X（2016)05-0076-03
作者:
 李晓飞; 邱晓晖
 南京邮电大学 通信与信息工程学院
Author(s):
 LI Xiao-fei; QIU Xiao-hui
关键词:
 ; 小波变换; 图像去噪; 小波阈值去噪; 阈值函数; 高斯噪声; 均方差; 峰值信噪比
Keywords:
 ; wavelet transform; image denoising; wavelet threshold denoising; threshold function; Gaussian noise; MSE;  PSNR
分类号:
TP301.6
文献标志码:
A
摘要:
 由于经典的小波阈值函数存在一定的缺陷,如硬阈值函数在阈值处不具有连续性,软阈值函数的小波估计系数和原系数之间存在着恒定的偏差,会导致去噪后的图像出现失真、产生吉布斯震荡等问题.文中综合典型的小波阈值函数的优点,并综合一些改进的方法,针对其缺点,提出了一种改进的阈值函数.该函数不仅在阈值处是连续的、小波估计的系数渐进原系数,并且具有可微性,易于实现梯度算法的自适应学习.为了验证该阈值函数的优越性,通过仿真实验对几种小波去噪方法的均方差(MSE)和峰值信噪比(PSNR)进行了对比.实验结果表明,用改进后的阈值函数进行去噪,无论是在视觉效果上,还是在均方差和峰值信噪比性能分析上均优于常用的阈值函数.
Abstract:
 As the classical wavelet thresholding function has certain defects,for example,the hard threshold function is not continuous at the threshold,and there is constant deviation between the original coefficient for soft-threshold function,which can cause image distortion after denoising and produce the problem such as Gibbs phenomena. An improved threshold function based on the advantages of the typical wavelet thresholding function and combined some improved methods is proposed. The function is not only continuous at the threshold,the estimated wavelet coefficients approaching the original coefficient,but also differential and easy to realize the adaptive learning of gradient algorithm. In order to verify the superiority of the thresholding function, through the simulation experiment, the Mean Square Error ( MSE) and Peak Signal-To-Noise Ratio ( PSNR) from several wavelet denoising methods are compared. According to the experimental results,this proposed method has better in visual effect and performance analysis for MSE and PSNR than the traditional threshold func-tions.

相似文献/References:

[1]杨亚 王铮 张素兰 郭飞飞.基于小波变换的多聚焦图像融合[J].计算机技术与发展,2010,(03):56.
　YANG Ya,WANG Zheng,ZHANG Su-lan,et al.Multi - focus Image Fusion Scheme Based on Wavelet Transform[J].,2010,(05):56.
[2]刘会英 张政保 文家福 李占德.一种带纠错编码的小波域自适应盲水印算法[J].计算机技术与发展,2010,(03):140.
　LIU Hui-ying,ZHANG Zheng-bao,WEN Jia-fu,et al.A Wavelet Domain Adaptive Blind Watermarking Algorithm with Error Correcting Encoding[J].,2010,(05):140.
[3]郭航宇 景晓军 尚勇.基于小波变换和数学形态法的车牌定位方法研究[J].计算机技术与发展,2010,(05):13.
　GUO Hang-yu,JING Xiao-jun,SHANG Yong.License Plate Location Method Based on Wavelet Transform and Mathematical Morphology[J].,2010,(05):13.
[4]钱颖雪 左洪福 李耀华.小波与傅里叶变换耦合的静电监测信号去噪法[J].计算机技术与发展,2009,(07):1.
　QIAN Ying-xue,ZUO Hong-fu,LI Yao-hua.Static Monitoring Signal De- noising by Wavelet and FFT[J].,2009,(05):1.
[5]赵兵.小波变换阈值降噪在电力负荷管理终端中的应用[J].计算机技术与发展,2009,(07):206.
　ZHAO Bing.Application of Wavelet Transform Threshold Noise Reduction in Load Management Terminal[J].,2009,(05):206.
[6]张登银 薄顺荣 许扬扬.边缘检测算法改进及其在QoE测定中的应用[J].计算机技术与发展,2009,(08):49.
　ZHANG Deng-yin,BO Shun-rong,XU Yang-yang.Improved Image Edge Detection Algorithm and Its Application in QoE Measurement[J].,2009,(05):49.
[7]朱良燕 毛军军 苗强 吴涛[].合肥市降水变化趋势分形特征分析与预测[J].计算机技术与发展,2009,(09):17.
　ZHU Liang-yan,MAO Jun-jun,MIAO Qiang,et al.Analysis of Precipitation Changes Trend Fractal Features and Forecasts in Hefei[J].,2009,(05):17.
[8]王树梅 王志成 蔡健.一种基于灰度形态学的小波域边缘检测算法[J].计算机技术与发展,2009,(01):32.
　WANG Shu-mei,WANG Zhi-cheng,CAI Jian.A Novel Edge- Detection Algorithm in Wavelet Gray - Scale Morphology[J].,2009,(05):32.
[9]单立场 蔡坤宝 王永东.多分辨率分析在HRV信号分析中的应用[J].计算机技术与发展,2008,(01):250.
　SHAN Li-chang,CAI Kun-bao,WANG Yong-dong.Application of Multi Resolution Analysis to HRV Signal Analysis[J].,2008,(05):250.
[10]邢丹俊 王继成.基于提升小波的自适应阈值图像去噪[J].计算机技术与发展,2008,(02):42.
　XING Dan-jun,WPNG Ji-cheng.Adaptive Threshold Based on Lifting Wavelet Transform for Image Denoising[J].,2008,(05):42.
[11]鄂旭[] [],毕佳娜[],侯建[],等. 一种车牌智能定位方法研究[J].计算机技术与发展,2014,24(10):124.
　E Xu[] [],BI Jia-na[],HOU Jian[],et al. Research on a License Plate Intelligent Localization Method[J].,2014,24(05):124.
[12]李智,张根耀,王蓓. 基于一种新的阈值函数的小波图像去噪[J].计算机技术与发展,2014,24(11):100.
　LI Zh,ZHANG Gen-yao,WANG Bei. Wavelet Image Denoising Based on a New Threshold Function[J].,2014,24(05):100.
[13]张方舟,王徐研,郝庆辉. 基于遗传分形编码的嵌入式小波图像编码算法[J].计算机技术与发展,2015,25(01):128.
　ZHANG Fang-zhou,WANG Xu-yan,HAO Qing-hui. Embedded Wavelet Image Coding Algorithm Based on a Genetic Fractal Coding [J].,2015,25(05):128.
[14]佳伟[],徐煜明[][],肖贤建[]. 基于小波变换和迭代反向投影的超分辨率算法[J].计算机技术与发展,2015,25(02):74.
　SONG Jia-wei[],XU Yu-ming[][],XIAO Xian-jian[]. A Super Resolution Algorithm Based on Wavelet Transform and Iterative Back Projection[J].,2015,25(05):74.
[15]汪慧兰,毛晓辉,杨晶晶,等. 融合小波变换和SIFT特征的商标检索方法[J].计算机技术与发展,2015,25(04):89.
　WANG Hui-lan,MAO Xiao-hui,YANG Jing-jing,et al. Trademark Retrieval Method Combining Wavelet Transform and SIFT Features[J].,2015,25(05):89.
[16]荣雁霞,邱晓晖. 基于小波变换的分块压缩感知算法[J].计算机技术与发展,2015,25(05):29.
　RONG Yan-xia,QIU Xiao-hui. Image Blocking Compressed Sensing Algorithm Based on Wavelet Transform[J].,2015,25(05):29.
[17]王树梅,张文斌. 小波变换在数字图像边缘探测中的应用[J].计算机技术与发展,2015,25(06):16.
　WANG Shu-mei,ZHANG Wen-bin. Application of Wavelet Transform in Edge Detection for Digital Image[J].,2015,25(05):16.
[18]卢曾新,曲大鹏,范铁生. 基于多普勒波和小波变换的图像置乱算法[J].计算机技术与发展,2015,25(07):138.
　LU Zeng-xin,QU Da-peng,FAN Tie-sheng. Image Scrambling Algorithm Based on Doppler and Wavelet Transform[J].,2015,25(05):138.
[19]尚福华[],柴艳领[],杜睿山[],等. 小波双线性插值算法在测井曲线相似中的应用[J].计算机技术与发展,2015,25(09):66.
　HANG Fu-hua[],CHAI Yan-ling[],DU Rui-shan[],et al. Application of Wavelet Bilinear Interpolation Algorithm in Well-logging Curve Similarity[J].,2015,25(05):66.
[20]段晓杰,张绍成,曲大鹏,等. 基于混沌和小波变换系数的数字图像水印算法[J].计算机技术与发展,2015,25(10):34.
　DUAN Xiao-jie,ZHANG Shao-cheng,QU Da-peng,et al. Digital Image Watermarking Algorithm Based on Chaos and Wavelet Transform Coefficient[J].,2015,25(05):34.

更新日期/Last Update: 2016-09-19