基于改进的Kriging插值算法去高密度椒盐噪声方法  

Method of Removing High-density Salt and Pepper Noise Based on Improved Kriging Interpolation Algorithm

作　　者：夏兴华[1] 王启卉 XIA Xinghua;WANG Qihui(School of Electrical and Control Engineering,Shenyang Jianzhu University,Shenyang 110168,China)

机构地区：[1]沈阳建筑大学电气与控制工程学院,沈阳110168

出　　处：《移动信息》2024年第11期302-304,共3页Mobile Information

摘　　要：针对传统降噪算法在处理含有高密度椒盐噪声的图像时效果不佳的问题,文中提出了一种基于Kriging插值算法的改进高密度椒盐噪声去除方法。该方法在保留Kriging插值算法核心思想的基础上,进行了相应的优化与改进,针对Kriging插值算法在窗口扩大时造成的计算偏差,可以在窗口扩大时融入反距离权重,得到新的插值权重,最终将图像噪声点处的值替换成插值。实验结果表明,对于含有10%~80%噪声密度的图像,该方法去除椒盐噪声的效果相对较强,能有效地消除椒盐噪声并重建图像的整体结构。Aiming at the poor effect of traditional noise reduction algorithms in processing images containing high-density salt and pepper noise,an improved high-density salt and pepper noise removal method based on Kriging interpolation algorithm is proposed in this paper.The method is optimized and improved accordingly on the basis of retaining the core idea of Kriging interpolation algorithm.Aiming at the calculation deviation caused by Kriging interpolation algorithm when the window expands,the inverse distance weight can be incorporated when the window expands to obtain a new interpolation weight,and finally the value at the image noise point is replaced by interpolation.The experimental results show that for images with 10%to 80%noise density,the method has a relatively strong effect on removing salt and pepper noise,which can effectively eliminate salt and pepper noise and reconstruct the overall structure of the image.

关 键 词：椒盐噪声 KRIGING插值 自适应 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]