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Image reconstruction for electrical capacitance tomography is to retrieve the permittivity distribution of processes with different dielectric materials inside from the measured capacitances outside. It is a typical inverse problem and has been always a challenge for its nonlinearity and ill-posedness. This paper explores the possibility of applying Tikhonov regularization, widely used for ill-posed problems, to the image reconstruction for electrical capacitance tomography. Two methods using different regularization matrices are investigated by using the simulated data, which are the standard Tikhonov regularization and the Tikhonov regularization based on the second order derivative operator. Results show that both the standard Tikhonov regularization and the Tikhonov regularization with the second order derivative operator do not provide reconstructions with qualities good enough. In order to improve this, a hybrid image reconstruction algorithm, which is based on the Tikhonov regularization with the reconstruction from the linear back projection as a constraint, is developed. Numerical results show that this hybrid image reconstruction algorithm takes advantages from both the linear back projection and the Tikhonov regularization and provide reconstructions better than those from the LBP and the Tikhonov regularization. © 2007 American Institute of Physics [ABSTRACT FROM AUTHOR]