提出了一种平稳多小波变换方法,该方法结合多小波和平稳小波变换在信号去噪方面的优点.给出了二维图像平稳多小波变换的mallat分解重构算法,并对红外图像的平稳多小波变换系数进行阈值处理实现图像去噪,仿真结果表明,相对于平稳标量小波变换和多小波的噪声抑制方法,此方法对噪声有更好的抑制作用,并尽可能多的保持目标的特征和细节.

A novel stationary multiwavelet transform (SMWT) method was proposed. The method possesses the good quality of both multiwavelet transform and stationary scalar wavelet on signal denoising. The mallat decompositing and reconstructing of 2D image based on SMWT was inferred. By thresholding the SMWT coefficients of noisy infrared image, the original image can be reconstructed. The simulation results show that the image denoising effect of this method has obvious superiority compared with scalar wavelet and general multiwavelet transform method. At the same time, the reconstructing image can preserve the characterisics of original image as many as possible.