摘要
针对传统硬阈值函数在阈值处的不连续、软阈值函数中小波系数与小波估计系数之间存在的恒定偏差问题,提出一种基于改进阈值函数的图像去噪算法。该算法结合改进阈值函数的优点,通过设置适当的调整参数动态选取固定阈值,增加调节因子来降低原小波系数和估计小波系数之间的恒定偏差,从而提高重构图像和原图像的逼近程度。改进后的阈值函数在阈值处满足连续性,同时满足函数的渐近性和高阶可导性。仿真结果表明,采用改进后的阈值函数进行图像去噪,视觉效果好,PSNR和SNR都提高了,MSE有所降低,去噪效果得到了优化。
Aiming at the discontinuity of the traditional hard threshold function at the threshold and the constant deviation between the original wavelet coefficient and the wavelet estimation coefficient in the soft threshold function,this paper proposed an image denoising algorithm based on the improved threshold function.This algorithm combined the advantages of the improved threshold function,dynamically selected the fixed threshold by setting appropriate adjustment parameters,and added the adjustment factors to reduce the constant deviation between the original wavelet coefficient and the estimated wavelet coefficient,thereby improving the degree of approximation of the reconstructed image and the original image.The improved threshold function satisfied continuity at the threshold while satisfying the asymptotic and higher order conductibility of the function.Simulation results show that the visual effect is good,while using the improved threshold function for image denoising.In comparison,both PSNR and SNR are improved,MSE is reduced,and the denoising effect is optimized.
作者
张绘娟
张达敏
闫威
陈忠云
辛梓芸
Zhang Huijuan;Zhang Damin;Yan Wei;Chen Zhongyun;Xin Ziyun(College of Big Data&Information Engineering,Guizhou University,Guiyang 550025,China)
出处
《计算机应用研究》
CSCD
北大核心
2020年第5期1545-1548,1552,共5页
Application Research of Computers
基金
贵州省自然科学基金资助项目(黔科合基础[2017]1047号)。
关键词
小波变换
阈值函数
阈值图像去噪
均方误差
峰值信噪比
信噪比
wavelet transform
threshold function
threshold image denoising
mean square error(MSE)
peak signal-to-noise ratio(PSNR)
signal-to-noise ratio(SNR)
