Compressive Sensing Approach with Double Layer Soft Threshold for ECVT Static Imaging

Electrical Capacitance Volume Tomography (ECVT) is a capacitance based tomography technology which is developed since its advantages on non-invasive properties, low energy, and portability. One of the challenge on developing this tomography technology is on its imaging algorithm. Naturally the imaging method forms under-determined linear system which is indicated by dimension of the measurement is much smaller compared to the projected value dimension. Mathematically it implies ill-posed inverse problem. Therefore Compressive Sensing framework is used to solve the corresponding inverse problem. To improve the accuracy of the predicted image reconstruction, new threshold approach, Double Layer Soft Threshold, is proposed and attached to the proposed Compressive Sensing based ECVT imaging method. The simulations results show that the proposed method is able to improve the conventional ECVT imaging method, Iterative Linear Back Projection (ILBP), by significantly eliminating the elongation error.