基于模糊阈值的小波函数去噪算法  

Wavelet Function Denoising Algorithm Based on Fuzzy Threshold

作　　者：黎道花 周骅 LI Daohua;ZHOU Hua(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学大数据与信息工程学院,贵阳550025

出　　处：《微处理机》2022年第4期49-52,共4页Microprocessors

摘　　要：针对图像在传输系统中会由于噪声造成接收端图像模糊的问题,提出一种小波变换图像去噪算法。算法基于模糊阈值函数,兼有硬阈值和软阈值两者的优点,能够动态地选取阈值。算法可使小波系数间存在的偏差产生自适应融合,降低原小波系数与估计小波之间的偏差程度,以此提高传输后重构图像的质量。通过仿真实验,将实验结果与实际图片进行对比分析,表明算法在实际的图片重构中获得了良好的效果,满足设计目标,具有一定的实际应用价值。Aiming at the problem that the image will be blurred at the receiving end due to noise in the transmission system,a wavelet transform image denoising algorithm is proposed.Based on fuzzy threshold function,the algorithm has the advantages of both hard threshold and soft threshold,and can dynamically select the threshold.The algorithm can adaptively fuse the deviations between wavelet coefficients,and reduce the deviation between the original wavelet coefficients and the estimated wavelet,so as to improve the quality of the reconstructed image after transmission.Through the simulation experiment,the experimental results are compared with the actual images,which shows that the algorithm has achieved good results in the actual image reconstruction,meets the design objectives,and has certain practical application value.

关 键 词：图像去噪 小波函数 模糊阈值 自适应融合 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]