By studying the reconstructed algorithms of Tikhonov regularization and the Newtons one-step error reconstructor (NOSER),a combined regularization algorithm is proposed. Two evaluation parameters of reconstructed algorithms,i.e. normalization mean square distance criterion(NMSD)and normalized mean absolute distance criterion(NMAD)are used to evaluate the results precision of inverse problem quantificationally. The comparison among Tikhonov regularization,NOSER and the combined regularization shows that the ill-condition and error of inverse problem are reduced. This new algorithm can decrease the condition number by 97%,NMSD by 51% and NMAD by 41% at least. Simulate results show that the combined regularization algorithm can reconstruct the target image in the depth from 10 mm to 40 mm. The performance of this system and the combined regularization algorithm demonstrate significantly better spatial resolution and less reconstructed error.