摘要
为了更有效地去除脉冲噪声,该文提出了一种迭代的自适应最小偏差滤波算法.该方法根据脉冲噪声的灰度特征、灰度的局部偏差以及局部统计特征进行噪声检测,自适应地根据邻域像素的局部偏差大小,用与邻域像素偏差最小的像素灰度作为当前噪声像素的新灰度.迭代且自适应地执行噪声去除,以适应不同噪声密度与噪声分布的局部不均匀性,并充分利用先前去噪处理的结果.实验结果表明,在峰值信噪比PNSR、边缘保持指数EPI和视觉感知以及计算效率上,所提出的方法优于现有的方法,具有更好的去噪性能和细节保持能力.
Aiming for more effective image restoration from impulse noise,an adaptive and iterative deviation filter is proposed,which uses a noise detector employing the intensity feature of impulse noise as well as local deviation and local statistics for noise detection,and an adaptive and iterative technique for noise removal,which removes noise by referring to the local deviation of neighboring pixels,taking one neighboring pixel with the smallest deviation with neighboring noise free pixels as the new intensity of noisy pixel.The noise removal technique performs adaptively and iteratively,so as to cater for various noise densities and local inhomogeneity of noise distribution,and make the most of the previously processed results.In terms of peak signal to noise ratio,edge preservation index,visual representation,and computational time,experimental results reveal and verify that the proposed method has better capability in noise removal and image details preservation than the state-of-the-art filters.
作者
张国明
李少义
ZHANG Guoming;LI Shaoyi(School of Information and Artificial Intelligence,Nanchang Institute of Science and Technology,Nanchang 330108,China;School of Materials Science and Engineering,Wuhan University of Technology,Wuhan 430205,China)
出处
《华中师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2023年第4期520-527,共8页
Journal of Central China Normal University：Natural Sciences
基金
国家自然科学基金项目(61562063,82274680)
江西省科技厅重点研发计划项目(20192BBEL50031)
江西省教育厅科学技术研究项目(GJJ202502).
关键词
图像滤波
脉冲噪声
噪声检测
开关中值滤波
局部偏差
局部统计特性
image denoising
impulse noise
noise detection
switching median filter
local deviation
local statistics
