摘要
针对小波硬阈值去噪函数的不连续和软阈值去噪函数的恒定偏差导致图像边缘模糊的缺点,本文提出了一种新的半软阈值函数。该方法通过区分图像的强弱边缘分别进行处理,并在弱边缘小波系数的估计中采取基于贝叶斯估计的方法且考虑了邻域小波系数的大小。仿真结果表明,与原有的小波阈值去噪算法和普通的阈值去噪算法相比,该算法在峰值信噪比(PSNR)、边缘保持指数(EPI)和视觉效果上都有明显的提高。该方法能够很好地保护图像边缘信息,达到很好的去噪效果。
The soft threshold function will produce a constant deviation cause and the hard threshold function is not continuous cause image edges blur.In this paper a new semi-soft threshold function method is proposed.This method processes the image by distinguish strong and weak edge.What＇s more,the neighboring wavelet coefficients and Bayesian estimation method were incorporated into the estimation of the weak edge.Simulation results showed that the proposed algorithm had better visual effect and PSNR and EPI performance than many exiting thresholding methods.This method can protect the edge of the image to achieve a good denoising effect.
出处
《国外电子测量技术》
2016年第4期42-45,共4页
Foreign Electronic Measurement Technology
基金
广东省科技计划项目(2013B090800022)
广东省科技计划项目(2015B090901047)资助
