Split Bregman algorithm based on adaptive parameter for planar array sensor imaging

Abstract

Planar array capacitance imaging is a visualization imaging technique based on the edge effect of electric fields. However, there are ill-posed problem and soft-field effects in the imaging process, which results in unstable and susceptible imaging. To address this issue, the inverse solution of planar array capacitive imaging system is transformed into an optimization problem with the approximate solution of linear-squares. A new cost function with total variation sparse reconstruction model is presented, which considers the sparsity of regularization operator to improve the stability of the inversion process. The adaptive split Bregman iterative algorithm is proposed to solve the inverse optimization problem. The computation is simplified by splitting the complex optimization problem into simple subproblems. The results show that the algorithm can obtain stable model updates, and numerical experiments prove the effectiveness and reliability of the algorithm.