计算机技术与发展2016，Vol.26Issue(5)：76-78,3.DOI:10.3969/j.issn.1673-629X.2016.05.016
基于小波变换的改进软阈值图像去噪算法
An Improved Soft-threshold Image Denoising Algorithm Based on Wavelet Transform
摘要
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.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Key words
wavelet transform/image denoising/wavelet threshold denoising/threshold function/Gaussian noise/MSE/PSNR分类
信息技术与安全科学引用本文复制引用
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(5):76-78,3.基金项目
江苏省自然科学基金(BK2011789) （BK2011789）
东南大学毫米波国家重点实验室开放课题(K201318) （K201318）
