小波检测的二次迭代修剪均值滤波算法

Twice iterative trimmed mean filter with wavelet detection

针对现有的算法对于高密度脉冲噪声的去除缺乏有效性和鲁棒性,难以有效地保持和恢复图像的边缘和细节结构,提出了一种小波检测的二次迭代修剪均值滤波方法。方法充分利用脉冲噪声的特征以及小波阈值去噪图像的高度相关性,根据灰度最值与小波阈值去噪图像进行噪声检测,先后分别用3×3和5×5邻域的迭代修剪均值滤波对噪声像素进行恢复。实验结果显示,相对于现有的最新提出的方法,所提出的方法获得更高的PSNR和EPI值,以及更好的视觉效果,具有优越的去噪性能和更好的细节结构保持能力。

Aiming at the existing methods being short of effectiveness and robustness for high density impulse noise removal,and failing to preserve and restore the edges and detail structures of image,a twice iterative trimmed mean filter with wavelet detection is proposed.This method takes full benefit of characteristic of impulse noise and the highly correlation of wavelet denoising image,identifies the noisy pixel with extreme intensity values and wavelet denoising image,and uses the iterative trimmed mean filter with 3×3 and 5×5 neighborhood successfully for noisy pixel restoration.The experimental results show that in comparison to existing methods proposed very recently,the proposed method achieves higher PSNR and EPI values,and better visual perception,showing superior capability in denoising and detail structure preservation.