In the applications of tomographic imaging,insufficient data reconstruction using few projections from limited angle is very important,because it would enable rapid scanning with reduced X-ray doses delivered to patients. The iterative image reconstruction algorithm based on the minimization of the image total variation (TV) works well for limited-angle reconstruction problem. However,the weighting parameter in the cost function can only be determined through considerable experimentation and the parameter attained is not always the optimum. An iterative image reconstruction algorithm based on multiplicative regularization method is introduced. The method obtains the advantages of the TV method by introducing the TV as a multiplicative factor in the cost function,and it can also self-adaptively adjust the regularization parameter during the iterative process. Simulation results show that the proposed algorithm works effectively.