Total fractional-order variation regularization based image reconstruction method for capacitively coupled electrical resistance tomography

Compared with electrical resistance tomography, capacitively coupled tomography (CCERT) is preferred since it avoids problems of electrode corrosion and polarization. However, reconstruction conductivity distribution still a great challenge for CCERT. To improve quality, this work proposes novel image method based on total fractional-order variation regularization. Simulation conducted several typical models studied. Robustness the proposed to noise also conducted. Additionally, performance quantitatively evaluated. We have carried out phantom experiment further verify effectiveness method. The results demonstrate that quality has been largely improved when compared images reconstructed by Landweber, Newton-Raphson Tikhonov methods. inclusion more accurately background much clearer even under impact noise.