【摘要】 由于金属表面的锈蚀,使得线条痕迹图像易受噪声影响,造成图像特征提取、比对和分析困难等问题。常用的去噪方法如高斯滤波易破坏边缘特征,形成边缘偏移,均值滤波不能够有效区分边缘与背景。为此,提出一种新的图像去噪算法。在以PM方程为扩散模型的偏微分方程滤波算法中,根据条纹的纹理特性,在不同扩散方向系数中引入不同权值,同时在迭代中依据图像的灰度直方图选取扩散门限。实验结果表明,线条痕迹图像降噪效果优于PM模型和林石算子,在处理线条痕迹图像中有较好的应用价值。更多还原

【Abstract】 Due to the rust on metal surface,it is easily to make the line trace images affected by noise,and causes the problem of the image feature extraction,comparison and analysis. Traditional denosing method like Gauss filter causes damage and excurtion to the edge while mean filter cannot distinguish between edge and background effectively.Therefore a newdenoising method is proposed in this paper. The diffusion model of this partial different equation filter algorithm is PMequation. According to the textural feature of striation mark image,the different weight functions in different diffusion directions are introduced. However,the diffusion threshold is set up via gray level histogram of image in this method. The method can eliminate image noise without destroying image edges simultaneously. Experimental results showthat the algorithm is superior to the PMequation and Lin Shi operator and it has good application value in line trace image processing.更多还原