小波模极大值在图像消噪中的应用

摘要

This paper proposes using wavelet modulus maxima de-noising method. Image containing noise is took discrete stationary wavelet transform, the noise standard deviation is estimated, changes in the form of Bayes-shrink threshold, and gets de-noising threshold formula. The paper judges the wavelet coefficients modulus maxima generated by the edge image in each scale wavelet coefficients of each sub-band, uses the adaptive multi-threshold to atrophy wavelet coefficients for non-image edge in each wavelet sub-band of all different scales. The stationary wavelet inverse transform of the image is performed after de-noising. Experimental results show that the proposed de-noising method has better effect.%提出利用小波模极大值进行图像消噪方法,对含噪声图像进行离散平稳小波变换和噪声标准差的估计,在Bayes-shrink阈值计算的基础上,得到消噪的阈值计算公式.对各尺度各子带的小波系数模极大值进行判断,获得由图像边缘产生的小波系数,使用自适应多阈值的方法在小波各尺度、各子带萎缩非图像边缘产生的小波系数.经平稳小波逆变换得到消噪后的图像.实验结果表明,与以前消噪方法相比,该方法具有更好的效果.