【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 net-work. The method attempts to reproduce the mapping between the degraded C-scan image and the high qualityone by training a RBF network. The inputs for training are the sub-images divided from C-scan image of flat-bot-tom hole of size 3mm and the output is the corresponding center in high quality image. After the network wastrained, the other C-scan images were used to verify the network. The results show that the network producesgood restored results, in which the noise is removed and the edges are deblurred. Comparing the restored resultsby the networks trained by the different sub-images, the sub-images with size 7×7, scanning step of 3 are deter-mined as the optimal inputs for training.更多还原