Abstract: There are noises and pseudo-pixels in the ultrasonic tomography of concrete due to the ill-posed nature of inversion problems and the errors introduced from the testing and computation.To reliably identify the defects from the ultrasonic tomography of concrete by enhancing the SNR of inversion images，there are two methods，two-dimensional median filtering and cluster analysis based on SOFM neural network，are used in the post-processing of inversion images.The example of application shows that the combined usage of median filtering and cluster analysis may suppress the noises in the local and connectivity areas and non-local non-connectivity areas.Meanwhile，it is also shown that the solution of the inversion image is greatly improved and the defects are detected more correctly and reliably.

摘要： 由于反演问题固有的不适定性以及测试和计算误差等原因，混凝土超声波层析图像中存在噪音和伪像。为了增强混凝土层析成像图像结果的信噪比，可靠辨识混凝土的内部缺陷，采用二维中值滤波和基于SOFM神经网络的聚类分析对反演结果进行图像后处理。应用实例表明，联合运用中值滤波和聚类分析的图像后处理方法，可以在局部连通和非局部非连通的区域内抑制噪音，明显改善反演图像的分辨率，有效提高缺陷识别的正确性和可靠性。