The image quality and computation speed are bounded up with regularization parameters. To improve the ill-posed property of the inverse problem of electrical impedance tomography (EIT), a novel approach, which is based on the product of the residual norm and the solution norm(PRS), is presented to optimize the Tikhonov regularization parameters of EIT. To verify the feasibility and effectiveness of the proposed method, five simulations of image reconstruction, together with a tank experiment, have been carried out with considering different sizes, locations, conductivity distributions and numbers of the target areas as well as the scenarios of the data with noises. The encouraging results demonstrate that the proposed optimization approach can identify the relatively optimal regularization parameter quickly and has better noise immunity, and it also enhances the quality of the reconstructed images significantly compared with the conventional L-curve method.