基于层间特性的多级小波收缩去噪算法

Multilevel Wavelet Shrinkage De-Noising Algorithm Based on Inter-Scale Dependency

该文提出了一种新的基于层间特性的多级小波收缩去噪算法 .该算法根据图像小波系数的层间相关特性来确定各层的收缩阈值 ,并将这些收缩阈值用于图像去噪 .实验表明 :该算法比传统的算法能更有效地减少噪声 ,获得更高的PSNR .同时 ,新的算法还能减少高质量图像中的噪声 .

In this paper, we proposed a new multilevel wavelet shrinkage algorithm basing on inter-scale dependency for removal noise from the images. The shrinkage thresholds are determined by the inter-scale dependency. Experimental results show that this algorithm is superior to the classical wavelet shrinkage methods and receives higher PSNR. Furthermore, it can remove noise from the high quality images.