一种空间自适应小波门限去噪算法

A spatially adaptive wavelet denoising algorithm

提出了一种空间自适应小波门限去噪算法,该算法在小波域对含噪小波系数做两次自适应去噪,两次自适应门限分别基于最大似然(ML)方差估计和最大后验概率(MAP)方差估计.仿真结果表明,该算法与其它自适应门限去噪算法相比,去噪后的图象具有更高的峰值信噪比(PSNR).

In this paper, we propose a new algorithm which performs adaptive denoising twice in wavelet domain. The adaptive thresholds are respectively based on ML and MAP estimates of the variance. Experimental result shows that this algorithm yields higher PSNR compared to other adaptive wavelet denoising algorithms.