摘要
在图像处理领域,小波阈值去噪技术凭借其卓越的噪声抑制和细节保留性能,得到了广泛应用.然而,传统的小波阈值函数在实际图像处理过程中,往往面临着阈值选择不当的问题,导致图像过度平滑或噪声残留,从而影响图像的质量和后续处理效果.为了解决这一问题,提出了一种改进的小波阈值函数.在传统软阈值和硬阈值的基础上,创新性地引入了平滑过渡的高阶可导函数,通过这种新的阈值函数设计,在抑制噪声的同时,更有效地保留图像的边缘和细节信息.实验结果表明,改进的小波阈值函数在多种噪声水平下均表现出显著的去噪效果,处理后的图像边缘更加清晰,伪影明显减少,视觉效果显著提升.
In the field of image processing,wavelet thresholding denoising technology has been widely applied due to its excellent performance in noise suppression and detail preservation.However,traditional wavelet threshold functions often face challenges in the practical image processing context,such as improper threshold selection,which leads to excessive smoothing or noise retention,thereby affecting the image quality and subsequent processing outcomes.To address this issue,this paper proposes an improved wavelet threshold function.This improvement builds on traditional soft and hard thresholding by innovatively introducing a higher-order differentiable function with smooth transitions.This new threshold function design effectively preserves image edges and details while suppressing noise.Experimental results demonstrate that the improved wavelet threshold function exhibits significant denoising effects under various noise levels.The processed images have clearer edges,significantly reduced artifacts,and markedly enhanced visual quality.
作者
关雪梅
田国刚
GUAN Xuemei;TIAN Guogang(Department of Information Management,School of Management,Liaoning University of International Business and Economics,Dalian 116052,China;Hualu Technology&Culture(Dalian)Co.Ltd.,Dalian 116023,China)
出处
《商丘师范学院学报》
2025年第9期21-25,共5页
Journal of Shangqiu Normal University
基金
大连市社科联规划课题(2025dlskzd184)。
关键词
图像处理
小波变换
阈值函数
图像去噪
image processing
wavelet transform
threshold function
image denoising
