Characterizing heterogeneous material parameters plays an extremely crucial role in the field of biomedical applications. However, classical implicit optimization inverse methods require treating the material parameters of each node or element after the discretization of structural finite elements as optimization variables, leading to a high number of optimization variables. Additionally, for nonlinear constitutive models with multiple material parameters, solving processes can result in an exponential growth of optimization variables. To address these issues, we propose an explicit optimization inverse method based on movable and deformable components. The proposed method only involves optimizing the geometric parameters and material parameters of movable and deformable components, significantly reducing the total number of optimization parameters and improving convergence. The feasibility of the explicit optimization method in reconstructing heterogeneous material fields is validated through numerical comparisons with implicit optimization methods. Furthermore, the explicit optimization method not only provides accurate reconstruction results when using full-field displacement inversion but also achieves precise material distribution when only utilizing boundary displacement measurements. The approach presented herein is expected to effectively enhance the accuracy and efficiency of characterizing the biomechanical properties of soft materials, overcoming the bottleneck issues in performance.