基于新阈值函数和小波分析的数字图像去噪方法

在数字图像处理过程中消除和减弱噪声对信号具有很重要的影响。中值滤波是传统的减少图像噪声,提高图像质量的可行方法。文章研究了中值滤波及其改进算法在图像去噪中的应用,基于小波分析基础理论和数字图像信号的小波变换分解重构原理,通过对小波分解系数选定恰当的阈值并进行阈值量化,基于小波分解后的高低频系数进行信号重构,从而有效去除或降低信号的噪声。本文采取的算法在MATLAB仿真平台进行了验证,结果表明,基于本文提出的阈值函数和小波分析处理方法对图像去噪具有更好的适应性,能够更好的改善数字图像的质量。

Digital Image Denoising Method Based on New Threshold Function and Wavelet Analysis

In the process of digital image processing,it is very important to eliminate and weaken the noise.Median filtering is a traditional feasible method to reduce image noise and improve image quality.In this paper,the application of median filter and its improved algorithm in image denoising is studied.Based on the basic theory of wavelet analysis and the principle of wavelet transform decomposition and reconstruction of digital image signal,the appropriate threshold value is selected and quantized by wavelet decomposition coefficient,the signal is reconstructed based on the high and low frequency coefficients after wavelet decomposition,so as to effectively remove or reduce the noise of the signal.The algorithm adopted in this paper is verified in MATLAB simulation platform,and the results show that the threshold function and wavelet analysis method based on this paper have better adaptability to image denoising,and can better improve the quality of digital image.