摘要
利用小波变换进行图像去噪目前始终是研究的热点。文章提出了一种改进小波阈值的图像去噪新算法。该算法根据软硬阈值函数的不同优点,并结合斜坡阈值技术对小波阈值函数进行了改进,将经小波分解以后的小波变换系数分三种情况进行讨论,有效地剔除了噪声信号的影响。在进行图像处理中,能够得到较低的均方误差和较高的信噪比,并且能有效地去除Gibbs效应,保留较多图像的边缘和细节信息。仿真实验结果表明该算法的去噪效果优于传统的软硬阈值方法去噪,取得了很好的去噪效果。
In image processing, applications wavelet-based image denoising algorithms is a hot point. In this paper,improved wavelet thresholding denoising is proposed. It has the advantage of soft and hard thresholding. Ramp threshold function is used too. The image is pro- cessed by wavelet thresholding denoising,we can have little minimizes the mean squared error and more signal-to-noise ratio, and the Gibbs effect can be eliminated effectively. Experiment results show that the proposed algorithm is better than the existing image denoising algo- rithms using soft and hard thresholding,and the operation is more simple and direct.
出处
《舰船电子工程》
2013年第1期55-56,60,共3页
Ship Electronic Engineering
基金
陆军军官学院科研学术基金项目信息化条件下战斗动态模型研究(编号:2011XYJJ-014)资助
关键词
图像去噪
小波变换
阈值
仿真
image denoising, wavelet transform, thresholding, emulation
