基于改进NLM的PCB图像去噪算法

A PCB image denoising algorithm based on improved NLM

针对工业生产中的PCB图像边缘信息缺失且携带有大量噪声,现有去噪算法效果不佳、计算量庞大、复杂度高等问题,提出了一种基于改进NLM的PCB图像去噪算法,旨在提高PCB图像的去噪质量。首先,采用基于形态学的权重自适应算法对PCB图像进行图像增强,使PCB图像保留较好的边缘信息;其次,引入特征匹配模型对增强后的PCB图像与原始PCB图像进行特征点匹配融合;最后,通过改进NLM算法的权重值对PCB图像进行去噪,得到最终的去噪图像。实验结果显示,与现有算法相比,所提算法更好地保留了PCB图像的边缘信息,去噪效果佳,显著改善了图像质量,增强了图像的鲁棒性,且提高了计算速度,降低了算法复杂度。

In order to solve the problems of PCB image edge information missing and carrying a lot of noise in industrial production,the existing de-noising algorithm has poor effect,large amount of calculation and high complexity.Based on this,a PCB image denoising algorithm based on improved NLM is proposed to enhance the denoising quality of PCB image.Firstly,the weight adaptive algorithm based on morphology is used to enhance the PCB image,so that the PCB image retains good edge information.Secondly,the feature matching model is introduced to fuse the enhanced PCB image with the original PCB image.Finally,the PCB image is denoised by improving the weight value of NLM algorithm,and the final denoised image is obtained.Experimental results show that,compared with the existing algorithms,the proposed algorithm retains the edge information of PCB image better,has better denoising effect,significantly improves the image quality,enhances the robustness of the image,improves the calculation speed and reduces the complexity of the algorithm.