面向缪子透射成像的BCD-NES算法

BCD-NES algorithm for muon transmission imaging

针对大规模缪子透射成像场景,提出一种基于块坐标下降(BCD)的缪子透射成像模型.设计具有抗噪能力的牛顿误差累积(NES)算法对该模型进行求解,构建一种面向缪子透射成像的BCDNES算法.该算法在求解缪子透射成像问题时能够避免对大规模优化问题的直接求解,显著降低计算复杂度和内存资源占用.仿真与实验结果表明,在有噪声和无噪声情形下,该算法均能有效实现对待测物体成像,还能避免实际应用中的异常体变形问题,弥补传统成像方法的不足.

For large-scale muon transmission imaging scenarios,a block coordinate descent(BCD)based muon transmission imaging model was proposed,and a noise-resistant Newton error summation(NES)method designed to solve the proposed model in order to construct a muon transmission imaging model.BCD-NES method for muon transmission imaging was constructed.The algorithm significantly reduced the computational complexity and memory resource consumption by avoiding the direct solution of the large-scale optimization problem when solving the muon transmission imaging problem.Simulation and experimental results showed that the proposed algorithm could effectively realize the imaging of the object to be measured both with and without noise interference,and it could avoid the problem of anomalous body deformation in practical applications and make up for the shortcomings of traditional imaging methods.