【摘要】 在充分考虑斑点噪声模型特殊性的基础上,将双变量收缩函数与小波系数显著性增强相结合,提出一种新的用于SAR图像的斑点抑制算法.将双变量收缩函数与双树复小波推广至斑点噪声模型,利用相邻尺度小波系数的联合概率密度函数与噪声的统计模型联立后,通过最大后验概率估计出滤波后图像的小波系数,再采用小波系数的模极大值准则对系数进行显著性增强,突出图像的边缘特征和点特征.仿真实验表明,与其他传统的去噪算法相比,该算法具有更好的去噪效果.更多还原

【Abstract】 Combining bivariate shrinkage function with enhancement of wavelet significant coefficients,a novel method is proposed for removing noise from images with speckle,which allows us to consider the particularity of the model for speckle noise.In our paper we make the speckle noise model suit the bivariate shrinkage function,and the joint probability density functions(PDF) and noisePDF could be united by MAP to de-noise image,then the wavelet coefficients are enhanced according to a rule whether the coefficient is a significant one or not.The simulation demonstrates that the new algorithm has a better denoised effect compared with other traditional denoising methods.更多还原