基于图像特征的各向异性扩散去噪方法

对图像去噪滤波方法,J.Weickert模型未考虑图像光滑区域与其他图像特征的区别,在光滑区域的扩散也按照局部结构特征值进行,因而在光滑区域不可避免地产生虚假边缘，为此，提出一种改进的各向异性扩散方法。该方法首先用维纳滤波减弱噪声对图像的影响,再利用相干性正确判断边缘区域、光滑区域和T形拐角等图像特征,并依据图像特征设置相应区域扩散张量的特征值。实验结果表明,改进方法在消除噪声和保护边缘方面能取得较好的效果,并有效消除光滑区域的虚假边缘,可得到较高的峰值信噪比。

Anisotropic diffusion denoising method based on image feature

As for the image denoising filter method,the model proposed by J.Weickert does not consider the distinctions between the smooth area and other image features.The diffusion in smooth area is also in accordance with the eigenvalues of local structure characteristics,thus inevitably producing false edges in smooth area.An improved anisotropic diffusion method was proposed.This method firstly used the Wiener filter to weaken the influence of noise on the image,then coherence was applied to judge image feature correctly,as edge region,smooth area,T-shape corner and so on,and the diffusion tensor’s eigenvalues in corresponding region were set based on image feature.The experimental results show that the improved method can not only achieve better results in elimination of noise and protection of edge,but also remove false edge in smooth area effectively and get higher peak signal-to-noise ratio.