【作者】 朱良峰； 曹宗杰； 吴勇； 薛锦； 王裕文；

【Author】 Zhu Liangfeng Cao Zongjie Wu Yong Xue Jin Wang Yuwen (Welding Research Institute, Xi’an Jiaotong University, Xi’an 710049, China)

【机构】 西安交通大学焊接研究所；

【摘要】 针对超声C扫描图像中存在噪声干扰和边界模糊而导致图像质量下降的问题,提出了一种基于径向基函数网络复原超声C扫描降质图像的方法。用φ3mm平底孔的超声C扫描降质图像对网络进行训练,建立了降质图像和复原图像之间的映射关系,并用其它降质图像验证了网络。试验结果表明,该网络能有效地消除图像中的噪声和边界模糊现象,使图像中尺寸更加接近实际尺寸。同时,通过对比三种不同网络的复原效果,得到了一个最佳网络参数。更多还原

【Abstract】 A method for restoration of ultrasonic C-scan images is presented by using a radial basis function network. The method attempts to reproduce the mapping between the degraded C-scan image and the high quality one by training a RBF network. The inputs for training are the sub-images divided from C-scan image of flat-bottom hole of size 3mm and the output is the corresponding center in high quality image. After the network was trained, the other C-scan images were used to verify the network. The results show that the network produces good restored results, in which the noise is removed and the edges are deblurred. Comparing the restored results by the networks trained by the different sub-images, the sub-images with size 7×7, scanning step of 3 are determined as the optimal inputs for training.更多还原